Have you ever wondered how our phones can transmit voices across the world in an instant? Or how a radio can play music from a distant station? The answer lies in the world of signals, and more specifically, analog signals. But what exactly are analog signals and how do they differ from digital signals? In this comprehensive guide, we will delve into the fascinating world of analog signals and explore their applications in our daily lives. Get ready to discover the technology that makes communication possible in the modern world!
What are Analog Signals?
Definition and Characteristics
Analog signals are continuous-time signals that can take on any value within a specified range. These signals are often used to represent physical phenomena, such as sound, temperature, and pressure. Unlike digital signals, which have distinct states that can be either 0 or 1, analog signals can be any value between two extreme values.
One of the key characteristics of analog signals is their ability to vary continuously over time. This means that the amplitude, frequency, or phase of an analog signal can change gradually or abruptly, depending on the nature of the underlying physical process.
Another important characteristic of analog signals is their susceptibility to noise and interference. Since analog signals are not digital, they can be easily corrupted by external factors such as electromagnetic interference, radio frequency interference, or thermal noise. This makes it important to design analog circuits that are robust and resistant to noise.
Analog signals also have a number of practical applications in fields such as audio, video, and telecommunications. For example, analog audio signals are used to transmit sound over long distances, while analog video signals are used to transmit television signals. In these applications, analog signals are often modulated or filtered to improve their quality or to reduce interference.
Overall, understanding the definition and characteristics of analog signals is crucial for anyone working in fields that involve signal processing, electronics, or telecommunications. By gaining a deep understanding of analog signals, engineers and scientists can design better circuits, optimize communication systems, and develop new technologies that rely on analog signal processing.
Applications of Analog Signals
Analog signals have a wide range of applications in various fields. Here are some of the most common applications of analog signals:
- Audio and Video: Analog signals are widely used in the transmission of audio and video signals. Analog TV signals are transmitted over the airwaves and are received by antennas. Analog audio signals are also used in many musical instruments and sound systems.
- Communications: Analog signals are used in telephone and radio communications. In telephone systems, analog signals are used to transmit voice signals over long distances. In radio communications, analog signals are used to transmit audio and video signals.
- Control Systems: Analog signals are used in control systems to regulate and control the operation of machines and equipment. For example, analog signals are used in industrial control systems to regulate the speed of motors and other equipment.
- Medical Devices: Analog signals are used in medical devices such as heart rate monitors, blood pressure monitors, and ECG machines. These devices use analog signals to measure and transmit vital signs to healthcare professionals.
- Scientific Research: Analog signals are used in scientific research to measure and record data. For example, analog signals are used in seismology to measure earthquakes and in physics to measure the behavior of materials.
Overall, analog signals have many applications in various fields and are an essential part of modern technology.
The Basics of Analog Signals
How Analog Signals Work
Analog signals are continuous signals that can take on any value within a range. They are often used to represent physical phenomena such as sound, light, and temperature. The strength or amplitude of an analog signal can change continuously over time, allowing for a wide range of values to be represented.
One of the key features of analog signals is that they can be transmitted over long distances without losing any information. This is because the signal is continuously varying and can be faithfully reproduced at the receiving end. In contrast, digital signals are discrete and can only take on specific values, making them more susceptible to degradation during transmission.
Analog signals are often represented using waveforms, which are plots of amplitude versus time. The shape of the waveform can provide information about the signal, such as its frequency content or duration. Different types of waveforms can be used to represent different types of signals, such as sine waves for audio signals and square waves for digital signals.
Analog signals can be processed using a variety of techniques, such as filtering and amplification. These techniques can be used to modify the signal in specific ways, such as removing noise or boosting the signal strength. Analog signal processing is used in a wide range of applications, from audio and video processing to telecommunications and control systems.
Overall, understanding how analog signals work is crucial for anyone working with electronic systems or signal processing. By understanding the basics of analog signals, you can gain a deeper appreciation for how these signals are used in a wide range of applications and how they can be manipulated to achieve specific goals.
Analog Signal Properties
Analog signals are continuous signals that vary in amplitude, frequency, or phase over time. These signals are used to represent physical phenomena such as sound, temperature, and pressure. The properties of analog signals are crucial in understanding how they behave and how they can be measured. The following are the key properties of analog signals:
- Continuous nature: Analog signals are continuous and do not have discrete values. They can take any value within a certain range, and they can change continuously over time.
- Waveform: Analog signals are often represented as waveforms, which are plots of amplitude versus time. The shape of the waveform can provide information about the signal’s frequency content and other characteristics.
- Amplitude: The amplitude of an analog signal represents the strength or intensity of the signal. It is the maximum deviation of the signal from its equilibrium or reference value.
- Frequency: The frequency of an analog signal represents the number of oscillations or cycles per second. It is measured in Hertz (Hz) and is an important property of signals such as sound and radio waves.
- Phase: The phase of an analog signal represents the position of the signal’s waveform relative to a reference point. It is measured in degrees and can be used to describe the timing of different signals.
- Distortion: Analog signals can be subject to distortion, which is a deviation from the ideal waveform. Distortion can be caused by a variety of factors, including electromagnetic interference, nonlinear components, and noise.
- Sensitivity: The sensitivity of an analog signal refers to its ability to detect small changes in the physical phenomenon being measured. High-sensitivity analog signals can detect small variations in temperature, pressure, or other physical quantities.
Understanding these properties is essential for working with analog signals in various applications, such as audio and video processing, control systems, and communications. By knowing how to measure and analyze these properties, engineers and scientists can design better analog circuits and systems that meet the needs of their applications.
Amplitude Modulation
Amplitude modulation (AM) is a method of transmitting information by varying the amplitude of a carrier wave in proportion to the amplitude of a modulating wave. The modulating wave, or message signal, is typically a low-frequency voice or music signal. The carrier wave is a high-frequency signal that is used to carry the modulated signal over long distances.
In AM, the amplitude of the carrier wave is increased or decreased in proportion to the amplitude of the modulating signal. This is achieved by varying the distance between the carrier wave and the modulating signal, which causes the amplitude of the carrier wave to vary in accordance with the amplitude of the modulating signal. The resulting signal is a modulated wave that contains both the information from the modulating signal and the carrier wave.
The process of AM can be represented mathematically as follows:
$f_c(t) = A_c + k_am * f_m(t)$
where $f_c(t)$ is the carrier wave, $A_c$ is the amplitude of the carrier wave, $k_am$ is the amplitude modulation coefficient, and $f_m(t)$ is the modulating wave.
The modulated signal can be demodulated by subtracting the carrier wave from the modulated signal, resulting in the original modulating signal:
$f_m(t) = f_c(t) – k_am * f_m(t)$
Amplitude modulation is used in a variety of applications, including radio and television broadcasting, telephone systems, and data transmission. It is a simple and effective method of transmitting information over long distances, but it is also susceptible to noise and interference, which can affect the quality of the signal.
Digital Signals vs. Analog Signals
Key Differences
Amplitude Modulation
Analog signals are typically characterized by continuous amplitude modulation, which means that the amplitude of the signal varies continuously with time. In contrast, digital signals have discrete amplitude levels that are used to represent binary digits (bits).
Continuous vs. Discrete Time
Analog signals are defined over a continuous time domain, whereas digital signals are defined over a discrete time domain. This means that analog signals can take on any value within a given range, while digital signals can only take on a finite number of discrete values.
Bandwidth
Analog signals have a much wider bandwidth compared to digital signals. This is because analog signals contain a continuous range of frequencies, while digital signals are typically restricted to a much narrower bandwidth.
Information Capacity
Analog signals have a lower information capacity compared to digital signals. This is because analog signals can only represent a limited range of values, while digital signals can represent an infinite number of discrete values.
Noise Immunity
Analog signals are more susceptible to noise and interference compared to digital signals. This is because noise and interference can cause the signal amplitude to deviate from its intended value, which can result in errors in the signal. Digital signals, on the other hand, are designed to be more resistant to noise and interference, as they can detect and correct errors in the signal.
Advantages and Disadvantages of Analog Signals
Analog signals have their own set of advantages and disadvantages that make them suitable for certain applications. Here’s a detailed look at the pros and cons of analog signals:
Advantages of Analog Signals:
- Continuous Range: Analog signals have a continuous range of values, making them well-suited for applications that require a continuous signal, such as audio and video signals.
- High Resolution: Analog signals can provide a high level of resolution, making them ideal for applications that require precise measurements, such as medical equipment and scientific instruments.
- Simple Circuitry: Analog signals can be transmitted using simple circuitry, making them cost-effective and easy to implement in many applications.
- Low Latency: Analog signals can be transmitted with low latency, making them ideal for real-time applications, such as audio and video streaming.
Disadvantages of Analog Signals:
- Susceptible to Interference: Analog signals are susceptible to interference from other signals, which can cause distortion and loss of information.
- Limited Bandwidth: Analog signals have a limited bandwidth, which means they cannot transmit a large amount of data over long distances.
- Difficult to Process: Analog signals can be difficult to process and require specialized equipment to interpret the signal.
- Susceptible to Noise: Analog signals can be affected by noise, which can degrade the quality of the signal and cause errors in measurement.
Overall, analog signals have their own set of advantages and disadvantages that make them suitable for certain applications. While they may not be as versatile as digital signals, they still have a valuable place in many industries and are used for a variety of purposes.
Analog Signal Processing
Filtering
In the field of analog signal processing, filtering plays a crucial role in enhancing the quality of analog signals. It involves the use of electronic circuits or digital algorithms to modify the amplitude, frequency, or time response of a signal. Filtering can be used to remove unwanted noise, emphasize specific frequency components, or to shape the signal to meet certain criteria.
There are various types of filters, including low-pass, high-pass, band-pass, and band-reject filters. Low-pass filters allow low-frequency signals to pass through while attenuating high-frequency signals, while high-pass filters do the opposite. Band-pass filters allow only a specific range of frequencies to pass through, while band-reject filters reject a specific range of frequencies.
The design of a filter depends on the desired frequency response and the specific application. In some cases, the filter may be designed to have a flat frequency response, while in others it may be designed to have a specific response that emphasizes certain frequency components.
One of the most commonly used filters in analog signal processing is the low-pass filter. It is used to remove high-frequency noise from a signal, such as in audio processing or image processing. The cutoff frequency of the filter determines the frequency at which the signal will be attenuated.
Another commonly used filter is the high-pass filter, which is used to remove low-frequency noise from a signal. This type of filter is commonly used in audio processing to remove bass frequencies or in video processing to remove flicker.
Filtering is a critical component in many analog signal processing applications, such as in audio and video processing, radio and television broadcasting, and medical imaging. Understanding the principles of filtering and the various types of filters available is essential for designing effective analog signal processing systems.
Sampling
Sampling is a critical aspect of analog signal processing that involves the process of measuring an analog signal at discrete intervals of time or space. The main objective of sampling is to convert a continuous-time analog signal into a discrete-time digital signal that can be processed by a computer or other digital devices.
There are two primary types of sampling: analog-to-digital (A/D) and digital-to-analog (D/A). In analog-to-digital sampling, an analog signal is sampled at regular intervals, and the sample values are then converted into digital form using an A/D converter. The sampling rate determines the frequency response of the system and the maximum frequency that can be sampled.
Digital-to-analog sampling, on the other hand, involves converting a digital signal back into an analog signal using a D/A converter. This process is used to interface digital devices with analog systems, such as audio systems or motor control systems.
The quality of the sampled signal depends on the sampling rate, which must be high enough to capture all the important features of the signal. A low sampling rate can result in aliasing, which is a phenomenon where high-frequency components of the signal are mistakenly interpreted as low-frequency components. This can lead to distortion and loss of information in the sampled signal.
Sampling is used in a wide range of applications, including audio and video processing, telecommunications, control systems, and biomedical engineering. Understanding the principles of sampling is essential for designing and implementing effective analog signal processing systems.
Quantization
Quantization is a process in which an analog signal is converted into a digital signal by sampling the signal at regular intervals and assigning a discrete value to each sample. The process of quantization is crucial in analog-to-digital conversion (ADC) and plays a vital role in the accuracy and quality of the digital signal.
There are several factors to consider when designing a quantization scheme, including the number of bits used to represent the signal, the sampling rate, and the range of values that the signal can take. In general, increasing the number of bits used to represent the signal increases the accuracy of the digital representation but also increases the amount of data that needs to be stored or transmitted.
One common quantization scheme is uniform quantization, in which the input signal is divided into a fixed number of intervals, and each interval is assigned a single digital value. Non-uniform quantization schemes, such as logarithmic or exponential quantization, are also used in certain applications to improve the accuracy of the digital representation.
In addition to the quantization scheme, the design of the quantizer itself is also important. A good quantizer should have a low distortion and minimize the loss of information in the original signal. This can be achieved through careful design of the quantization matrix or by using adaptive quantization techniques that adjust the quantization levels based on the characteristics of the input signal.
Overall, quantization is a critical step in the analog-to-digital conversion process and plays a significant role in the accuracy and quality of the resulting digital signal. Understanding the principles of quantization and the different quantization schemes available is essential for anyone working with analog signals in a digital context.
Analog Signal Transmission
Transmission Lines
Transmission lines refer to the physical pathways through which analog signals are transmitted from one point to another. They are used to transport electrical signals over long distances, such as in communication systems, electronic devices, and power distribution networks. The characteristics of transmission lines play a crucial role in determining the quality and reliability of analog signal transmission.
There are two main types of transmission lines:
- Balanced Lines: These are lines in which the signal is transmitted between two conductors that are equal in impedance. The most common type of balanced line is the twisted pair, which consists of two insulated wires twisted together. Twisted pairs are commonly used in telephone lines and Ethernet cables.
- Unbalanced Lines: These are lines in which the signal is transmitted between a single conductor and a grounded conductor. The most common type of unbalanced line is the coaxial cable, which consists of a central conductor surrounded by an insulating layer, a braided shield, and an outer insulating layer. Coaxial cables are commonly used in cable television and radio frequency (RF) applications.
The characteristics of transmission lines, such as their length, impedance, and interference, can affect the quality and reliability of analog signal transmission. Proper design and maintenance of transmission lines are essential to ensure optimal performance and prevent signal degradation or loss.
It is important to note that while digital signals can be transmitted over analog lines, analog signals cannot be transmitted over digital lines without proper conversion and encoding. This is because analog signals are continuous and vary in amplitude, whereas digital signals are discrete and represented by binary code.
Signal Integrity
Signal integrity refers to the ability of an analog signal to maintain its original form and strength as it travels through a system. In other words, it is the measure of how well an analog signal maintains its fidelity and strength over time and distance. The quality of the signal is affected by various factors such as noise, interference, and crosstalk.
To ensure optimal signal integrity, it is important to understand the factors that can affect it. Here are some of the key factors that can impact signal integrity:
- Noise: Noise is any unwanted signal that can disrupt the original signal. It can be caused by various sources such as electromagnetic interference (EMI), radio frequency interference (RFI), and thermal noise.
- Interference: Interference is any signal that can disrupt the original signal. It can be caused by various sources such as nearby electronic devices, power lines, and other signals in the environment.
- Crosstalk: Crosstalk is the unwanted transfer of signal energy from one circuit to another. It can be caused by various sources such as proximity and electromagnetic fields.
- Distance: The distance between the source of the signal and the receiver can also impact signal integrity. The farther the distance, the more the signal can degrade.
- Frequency: The frequency of the signal can also impact signal integrity. Higher frequency signals are more susceptible to noise and interference.
To ensure optimal signal integrity, it is important to design systems that minimize the impact of these factors. This can be achieved through various techniques such as shielding, filtering, and impedance matching. By minimizing the impact of these factors, it is possible to maintain the fidelity and strength of the analog signal, ensuring that it is received accurately and reliably.
Signal Distortion
Introduction to Signal Distortion
Signal distortion refers to the alteration of an analog signal’s waveform, often caused by factors such as noise, interference, or imperfect transmission. In analog communication systems, signal distortion can significantly impact the quality and reliability of the transmitted information. Understanding the causes and effects of signal distortion is crucial for optimizing the performance of analog communication systems.
Causes of Signal Distortion
Several factors can contribute to signal distortion in analog communication systems, including:
- Noise: Unwanted signals or interference can introduce noise into the system, which can corrupt the original signal and lead to distortion.
- Interference: External electromagnetic signals or radio-frequency interference can cause interference in the system, affecting the quality of the transmitted signal.
- Non-linear components: Non-linear components in the system, such as diodes or transistors, can introduce distortion due to their non-linear response to input signals.
- Insufficient bandwidth: Inadequate bandwidth can result in signal distortion, as the signal may be unable to occupy the entire frequency spectrum, leading to frequency overlap and interference.
- Inadequate power supply: A weak power supply can cause distortion by affecting the performance of active components in the system.
Effects of Signal Distortion
Signal distortion can have several adverse effects on the performance of analog communication systems, including:
- Increased bit error rate (BER): Signal distortion can cause errors in the transmission of digital data, leading to an increased bit error rate (BER).
- Reduced signal-to-noise ratio (SNR): Signal distortion can decrease the signal-to-noise ratio (SNR), making it more difficult to detect the desired signal amidst the noise.
- Impaired system capacity: Signal distortion can limit the capacity of the communication system, as it may require additional resources to recover and compensate for the distorted signal.
- Increased interference and intermodulation: Signal distortion can exacerbate interference and intermodulation, leading to further degradation of the signal quality.
Mitigating Signal Distortion
To mitigate signal distortion in analog communication systems, several techniques can be employed, including:
- Filtering: Using appropriate filters to remove noise and interference from the signal can help reduce signal distortion.
- Equalization: Applying equalization techniques can help compensate for distortion caused by insufficient bandwidth or other factors.
- Signal amplification: Increasing the power supply to the system can improve the performance of active components and reduce distortion.
- Non-linear distortion compensation: Using non-linear devices or algorithms to compensate for the distortion introduced by non-linear components can improve system performance.
- Digital signal processing (DSP): Employing digital signal processing techniques, such as channel equalization or noise reduction, can help mitigate the effects of signal distortion in hybrid or digital communication systems.
By understanding the causes and effects of signal distortion, as well as implementing appropriate mitigation techniques, engineers can optimize the performance of analog communication systems and ensure reliable transmission of information.
The Future of Analog Signals
Emerging Trends
The field of analog signals is constantly evolving, and there are several emerging trends that are worth noting. Here are some of the most significant ones:
- Increased use of wireless technologies: As wireless technologies continue to improve, it is likely that analog signals will become increasingly popular for wireless communication. This is particularly true for applications that require high bandwidth and low latency, such as wireless audio and video streaming.
- Integration with digital systems: As digital systems become more prevalent, there is a growing trend towards integrating analog signals with digital systems. This is particularly true for applications that require real-time data acquisition and processing, such as industrial automation and medical imaging.
- Use in emerging technologies: There are several emerging technologies that are driving the use of analog signals, including the Internet of Things (IoT), autonomous vehicles, and robotics. These technologies require sophisticated signal processing and analysis, which makes analog signals an essential component.
- Environmental monitoring: As the world becomes increasingly concerned with environmental issues, there is a growing need for reliable and accurate environmental monitoring systems. Analog signals are well-suited for this application, as they can provide real-time data on a wide range of environmental parameters, such as temperature, humidity, and air quality.
- Artificial intelligence and machine learning: As artificial intelligence and machine learning become more prevalent, there is a growing need for real-time data analysis and processing. Analog signals are well-suited for this application, as they can provide high-bandwidth, real-time data that can be used to train machine learning models and improve the accuracy of AI systems.
Challenges and Limitations
While analog signals have been an integral part of many communication systems for decades, there are several challenges and limitations that need to be addressed in the future. Some of these challenges include:
- Interference and noise: One of the biggest challenges facing analog signals is interference and noise. Interference can be caused by a variety of factors, including electromagnetic interference (EMI), radio frequency interference (RFI), and crosstalk. Noise can also degrade the quality of the signal and make it difficult to detect.
- Bandwidth limitations: Another challenge facing analog signals is bandwidth limitations. Analog signals require a certain amount of bandwidth to transmit, and this bandwidth can be limited by the available infrastructure. As more devices are added to the network, the available bandwidth can become saturated, leading to reduced signal quality and dropped connections.
- Security concerns: As analog signals are transmitted over the airwaves, they can be intercepted by unauthorized parties. This can lead to security concerns, particularly in military and defense applications where secure communication is essential.
- Maintenance and repair: Analog signals require regular maintenance and repair to ensure optimal performance. This can be time-consuming and costly, particularly for large-scale communication systems.
- Compatibility issues: Finally, there may be compatibility issues between different types of analog signals and systems. This can make it difficult to integrate new technology into existing systems, leading to a slower adoption rate and higher costs.
Overall, while analog signals have been a reliable and effective means of communication for many years, there are several challenges and limitations that need to be addressed in the future. As technology continues to evolve, it will be important to find ways to overcome these challenges and ensure that analog signals remain a viable option for communication systems.
FAQs
What is the difference between analog and digital signals?
Analog signals are continuous signals that can take on any value within a range, while digital signals are discrete signals that can only take on specific values. Analog signals are often used to represent physical phenomena, such as sound or temperature, while digital signals are used to represent information, such as data or computer instructions.
How are analog signals used in electronics?
Analog signals are used in a wide range of electronic devices, including audio and video equipment, medical equipment, and industrial control systems. They are often used to transmit information about physical phenomena, such as sound or temperature, that can be measured and converted into an electrical signal.
What are some advantages of analog signals over digital signals?
Analog signals have several advantages over digital signals, including their ability to convey a continuous range of values and their lower susceptibility to noise and interference. They are also typically easier to generate and process than digital signals.
What are some disadvantages of analog signals?
Analog signals have several disadvantages, including their susceptibility to noise and interference, which can cause distortion and loss of information. They are also more difficult to multiplex and switch than digital signals, which can limit their use in some applications.
What is the future of analog signals?
The future of analog signals is likely to be focused on improving their performance and reliability in a variety of applications. This may involve developing new technologies for reducing noise and interference, as well as improving the accuracy and resolution of analog-to-digital converters. Additionally, there may be new applications for analog signals in emerging fields, such as quantum computing and biomedical engineering.
FAQs
1. What are analog signals?
Analog signals are continuous signals that can take on any value within a range. They are often used to represent physical phenomena such as sound, temperature, and pressure.
2. What is the difference between analog and digital signals?
Analog signals are continuous signals that can take on any value within a range, while digital signals are discrete signals that can only take on specific values. Digital signals are typically represented as a series of 1s and 0s.
3. Can signals be both analog and digital?
Yes, signals can be both analog and digital. For example, an analog signal can be converted into a digital signal using an analog-to-digital converter (ADC). Similarly, a digital signal can be converted into an analog signal using a digital-to-analog converter (DAC).
4. What are some examples of analog signals?
Examples of analog signals include sound waves, temperature readings, and pressure measurements. These signals are continuous and can take on any value within a range.
5. What are some examples of digital signals?
Examples of digital signals include binary data, computer instructions, and video streams. These signals are discrete and can only take on specific values.
6. What are the advantages of analog signals?
Analog signals have several advantages, including their ability to represent a wide range of values and their resistance to noise and interference. They are also relatively simple to transmit and can be easily modulated to carry additional information.
7. What are the disadvantages of analog signals?
Analog signals have several disadvantages, including their susceptibility to noise and interference, their limited bandwidth, and their inability to transmit large amounts of data.
8. What are the advantages of digital signals?
Digital signals have several advantages, including their ability to transmit large amounts of data, their resistance to noise and interference, and their ability to be easily processed and manipulated.
9. What are the disadvantages of digital signals?
Digital signals have several disadvantages, including their requirement for a high sampling rate and the need for additional circuitry to convert them into analog signals. They can also be susceptible to errors due to quantization and digital noise.
10. How are analog signals transmitted?
Analog signals can be transmitted using a variety of methods, including radio waves, infrared light, and electrical cables. They can also be modulated to carry additional information.
11. How are digital signals transmitted?
Digital signals can be transmitted using a variety of methods, including wired and wireless communication. They are typically represented as a series of 1s and 0s and can be transmitted over long distances with minimal loss of data.
12. Can analog signals be converted into digital signals?
Yes, analog signals can be converted into digital signals using an analog-to-digital converter (ADC). This allows the signal to be processed and transmitted as a digital signal.
13. Can digital signals be converted into analog signals?
Yes, digital signals can be converted into analog signals using a digital-to-analog converter (DAC). This allows the signal to be processed and transmitted as an analog signal.
14. What is the difference between analog modulation and digital modulation?
Analog modulation involves varying the amplitude, frequency, or phase of an analog signal to carry additional information. Digital modulation involves encoding digital data into an analog signal using techniques such as amplitude shift keying (ASK) or frequency shift keying (FSK).
15. What is the difference between amplitude and frequency modulation?
Amplitude modulation (AM) involves varying the amplitude of a carrier signal in proportion to the modulating signal. Frequency modulation (FM) involves varying the frequency of a carrier signal in proportion to the modulating signal.
