What is digital signal processing (DSP)? – A complete overview

What is a Digital Signal Processing System?

• Let’s start with the individual meaning of the words defining Digital Signal Processing in its entirety.
  • Digital: In digital communication, we use discrete signals to represent data using binary numbers.
  • Signal: A signal is anything that carries some information. It’s a physical quantity that conveys data and varies with time, space, or any other independent variable. It can be in the time/frequency domain. It can be one-dimensional or two-dimensional. Here are all the major types of signals.
  • Processing: The performing of operations on any data in accordance with some protocol or instruction is known as processing.
  • System: A system is a physical entity that is responsible for the processing. It has the necessary hardware to perform the required arithmetic or logical operations on a signal. Here are all the major types of systems.
• Putting all these together, we can get a definition for DSP.

What is Digital Signal Processing (DSP)?

Digital Signal Processing is the process of representing signals in a discrete mathematical sequence of numbers and analyzing, modifying, and extracting the information contained in the signal by carrying out algorithmic operations and processing on the signal.

Block diagram of a DSP system

• The first step is to get an electrical signal. The transducer (in our case, a microphone) converts sound into an electrical signal. You can use any transducer depending upon the case.
• Once you have an analog electrical signal, we pass it through an operational amplifier (Op-Amp) to condition the analog signal. Basically, we amplify the signal. Or limit it to protect the next stages.
• The anti-aliasing filter is an essential step in the conversion of analog to a digital signal. It is a low-pass filter. Meaning, it allows frequencies up to a certain threshold to pass. It attenuates all frequencies above this threshold. These unwanted frequencies make it difficult to sample an analog signal.
• The next stage is a simple analog-to-digital converter (ADC). This unit takes in analog signals and outputs a stream of binary digits.
• The heart of the system is the digital signal processor. These days we use CMOS chips (even ULSI) to make digital signal processors. In fact, modern processors, like the Cortex M4 have DSP units built inside the SoC. These processor units have high-speed, high data throughputs, and dedicated instruction sets.
• The next stages are sort of the opposite of the stages preceding the digital signal processor.
• The digital-to-analog converter does what its name implies. It’s necessary for the slew rate of the DAC to match the acquisition rate of the ADC.
• The smoothing filter is another low-pass filter that smoothes the output by removing unwanted high-frequency components.
• The last op-amp is just an amplifier.
• The output transducer is a speaker in our case. You can use anything else according to your requirements.

Applications of a Digital signal processing system

We use digital signal processing in:

• Telecommunication
  • For echo cancellation.
  • Equalization – Think about tuning your radio for bass and treble).
  • Filtering – Removing unwanted signals using specially designed filters like the Infinite Impulse Response  Filter (IIR).
  • Multiplexing and repeating signals.
• Instrumentation and Control
  • In designing Phase Locked Logic (PLL).
  • Noise reduction circuits.
  • Compression of signals.
  • Function generators.
• Digital Image Processing
  • Compression of an image.
  • Enhancement, reconstruction, and restoration of an image.
  • Analysis or face detection (like Snapchat).
• Speech Processing
  • Digital audio synthesis.
  • Speech recognition and analysis.
• Medicine
  • X-rays, ECGs, EEGs.
• Signal filtering
  • Noise removal and shaping of signal spectrums.
• Military
  • Sonar and navigation.
  • Analysis after tracking in radars.
• Consumer electronics
  • Music players
  • Professional music turntables (like the ones DJs use).

Advantages of a Digital Signal Processing system

A digital signal processing system enjoys many benefits over an analog signal processing system. Some of these advantages are briefly outlined below:

• Less overall noise
  • Since the signals are digital and inherently possess a low probability of getting mixed with unwanted signals, the entire system benefits. Thus, DSPs don’t really have as much noise to deal with comparatively.
• Error detection and correction is possible in DSPs
  • Again, the presence of digital signal means we have access to many error detection and correction features. For example, we can use parity generation and correction as a detection and correction tool.
• Data storage is easier
  • Yet again, an advantage because of digital signals. You know how easy it is to store digital data, right? We can choose from a wide plethora of digital memories. However, analog data needs to be stored in tapes and stuff like that. It’s harder to transport and recreate with 100% fidelity.
• Encryption
  • Digital signals are easy to encrypt. So this one counts as a win for the entire DSP system too.
• Easier to process
  • Digital signals can easily undergo mathematical changes as compared to their analog counterparts.
• More data transmission
  • Time-division multiplexing is a great tool available for digital systems to transmit more data over unit time and over a single communication path.
• Higher component tolerance in DSP
  • The components like resistors, capacitors, and inductors have a certain threshold in terms of temperature. Outside this threshold, as the temperature increases, they might start behaving erratically.
  • These components are not present in a digital system. Moreover, digital systems can increase their accuracy with concepts like floating-point arithmetic.
• Easier to modify
  • To modify an analog processing system, you need to change components, test, and verify the changes. With digital processing systems, you just need to change a few commands or alter a few lines of code.
• DSP systems can work on frequencies of a broader range
  • There are some natural frequencies, like seismic frequencies that detect earthquakes. These signals have very low frequencies. Traditional analog signals might not even detect these signals. However, digital signal processing systems are adept at picking up even the tiniest of disturbances and also process them easily.
• Cost
  • When working at scale, DSPs are cheaper.

Disadvantages of a Digital Signal Processing system

• Complexity
  • As we saw in the block diagram above, there are a lot of elements preceding and following a Digital Signal Processor. Stuff like filters and converters add to the complexity of a system.
• Power
  • A digital signal processor is made up of transistors. Transistors consume more power since they are active components. A typical digital signal processor may contain millions of transistors. This increases the power that the system consumes.
• Learning curve and design time
  • Learning the ins and outs of Digital Signal processing involves a steep learning curve. Setting up digital processing systems thus takes time. And if not pre-equipped with the right knowledge and tools, teams can spend a lot of time in setting up.
• Loss of information
  • Quantization of data that is below certain Hz causes a loss in data according to the Rate-Distortion Theory.
• Cost
  • For small systems, DSP is an expensive endeavor. Costing more than necessary.

With the basic knowledge of the concept, you are now ready to dive right into our digital signal processing course.