Differences - Digital Signal Processing

# Differences - Digital Signal Processing | Signals and Systems - Electronics and Communication Engineering (ECE) PDF Download

Differances

UNIT-V

 Non Recursive filters Recursive filters for causal systemFor causal i/p sequence It gives FIR o/p. All zero filter. Always stable. for causal systemIt gives IIR o/p but not always.Ex: y(n) = x(n) – x(n-3) + y(n-1)General TF : H(z) =  bk = 0 for Non RecursiveNf= 0 for causal system

 FIR filters IIR filters 1. Linear phase no phase distortion. Linear phase, phase distortion. 2. Used in speech processing, data transmission & correlation processing Graphic equalizers for digital audio, tone generators filters for digital telephone 3. Realized non recursively. Realized recursively. 4. stable Stable or unstable.H(n) = an u(n)   a<1 stable=  0          a>1 unstable 5. filter order is more Less 6. more co-efficient storage Less storage 7. Quantization noise due to finite precision arithmetic can be made negligible Quantization noise 8. Co-efficient accuracy problem is More less severe 9. used in multirate DSP (variable sampling rate)

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## FAQs on Differences - Digital Signal Processing - Signals and Systems - Electronics and Communication Engineering (ECE)

 1. What is digital signal processing?
Ans. Digital Signal Processing (DSP) is a technique used to manipulate and analyze digital signals. It involves the use of algorithms to modify and extract information from digital signals such as audio, video, or sensor data. DSP is widely used in various fields, including telecommunications, audio and video processing, medical imaging, and radar systems.
 2. How does digital signal processing differ from analog signal processing?
Ans. The main difference between digital signal processing and analog signal processing is the representation of the signals. In analog signal processing, signals are continuous and represented by physical quantities such as voltage or current. On the other hand, digital signal processing deals with discrete-time signals that are represented by a sequence of numbers. DSP allows for precise and flexible manipulation of signals using mathematical operations, while analog signal processing relies on analog circuitry.
 3. What are the advantages of digital signal processing?
Ans. Digital signal processing offers several advantages over analog signal processing. Firstly, it provides greater accuracy and precision due to the use of mathematical algorithms. Additionally, DSP allows for the implementation of complex signal processing operations in a compact and cost-effective manner using digital hardware or software. Digital signals can also be easily stored, transmitted, and processed using computers, making DSP more versatile and efficient compared to analog signal processing.
 4. What are some common applications of digital signal processing?
Ans. Digital signal processing finds applications in a wide range of fields. Some common applications include audio and speech processing, image and video processing, wireless communication systems, radar and sonar systems, biomedical signal processing, and control systems. DSP is also extensively used in digital audio players, smartphones, digital cameras, and various consumer electronics devices for signal enhancement, noise reduction, and compression.
 5. What are the key components of a digital signal processing system?
Ans. A digital signal processing system typically consists of three key components: a sensor or transducer to convert analog signals into digital form, a digital signal processor (DSP) or microprocessor to perform the signal processing operations, and a digital-to-analog converter (DAC) to convert the processed digital signals back into analog form. Additionally, the system may also include analog and digital filters, memory units, and interfaces for data input/output.

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