Analog signal is a continuous signal, so if you take any time value, there is a defined value in the range. For example, if we divide a second into billion pieces, each and every piece of time has a value in the range. So, the signals are precise and accurate, unless it’s distorted when transferring them.
Moreover, analog signals are made of varying voltages or currents. For that reason, when we try to transfer those signals through wires, we have to face some problems. As we know, there are no perfect wires, so there is a resistance that creates a voltage drop. And when the wire is subjected to a magnetic field, it distorts the waveform.
To mathematically represent analog signals, we use a combination of sine waveforms. And we use the Fourier Series and Fourier Transformation to derive the equations.
Examples of analog signals
- Microphones generate voltage variation
- Even digital signals when they’re transferring (WiFi, FM, TV)
- Analog phones also generate a voltage variation and send it to the other side
- Temperature to varying voltage using thermometer
Digital signals are discrete signals which only have values for the defined points. For example, if we divide one second into 10 pieces, and store some values in each piece of time, there will be only those 10 values. So, there will be no value in the range in between an interval.
Digital signals are so useful in the modern world. The biggest advantage is the ability to transfer, modify and store without much data loss. It does not affect by noise, since it’s transferred as binary numbers.
Examples of digital signals
- Stored audio files are saved as digital signals.
- When we play recorded music, it’s a digital signal.
- Cable TV are most likely digital signals
- Internet is made of digital signals.
Analog vs Digital signals
The continuity is what makes analog and digital signals are different. In a digital signal, we only have a finite range of values for the range. But, in analog signals, both the time axis and the range are continuous, and each and every value in the time domain have a value in the range.
Editing and processing: It’s easier to edit and process digital signals. Since they’re in binary form, we can do different operations while saving the signal.
Content: Analog signal uses the change in voltage or current over time to represent the signal. And the digital signals use binary numbers to represent the signal.
Storage: Digital signals are in binary format and most of the modern data storage systems are digital and use a binary system. On the other hand, analog signals can be stored in analog storage devices such as cassette tapes. But these analog storage devices have problems such as the difficulty to edit, process, and rewrite.
Accuracy: Theoretically, digital signals are less accurate since they’re discontinuous. But in practical applications, it’s the opposite. Analog storage devices have practical difficulties to store the data precisely. When it comes to digital signals, it can be used to store data for each one over billion seconds.
For example, the maximum frequency we can hear is considered as 20kHz. And if we store data for a much higher frequency, there is no quality drop.
Noise: Analog are easily subjected to noise and get distorted. That’s why we hear noise in analog phones and see noises on the tv screens. But the digital signals don’t get distorted so easily since they’re transferred as binary units.
Error identification: When an analog signal is corrupted, it’s difficult to find out whether it’s corrupted or not. But when a digital signal is corrupted, it can be easily identified using computer software.
Discrete time signals and Digital signals
All the digital signals are discrete-time signals but not all the discrete-time signals are digital signals. Only the discrete-time signals with a finite number of distinct values are digital signals.