Eminent Engineering Interview Questions and Answers

Digital Signal Processing has applications in various fields such as telecommunications, audio and video processing, radar and sonar systems, medical imaging, and speech recognition.

• Telecommunications: DSP is used for signal compression, error detection and correction, and modulation and demodulation techniques.

• Audio and video processing: DSP is used for audio and video compression, noise reduction, and enhancement of audio and video quality.

• Radar and sonar systems: DSP is us...read more

Digital Signal Processing offers advantages over Analog Signal Processing

• DSP allows for greater accuracy and precision in signal processing

• DSP can be easily programmed and reprogrammed for different applications

• DSP can handle complex algorithms and computations more efficiently

• DSP can eliminate noise and interference more effectively than analog processing

• DSP can be integrated with other digital systems for seamless communication

• DSP can provide real-time processing and analys...read more

Basic elements of a digital signal processing system include analog-to-digital conversion, digital filters, and signal processing algorithms.

• Analog-to-digital conversion: Converts continuous analog signals into discrete digital signals for processing.

• Digital filters: Used to remove unwanted noise or enhance specific frequencies in the signal.

• Signal processing algorithms: Algorithms used to analyze, manipulate, and extract information from digital signals.

• Examples: FIR filters...read more

DSP in speech is used for speech recognition, enhancement, synthesis, and compression.

• Speech recognition: converting speech to text for applications like virtual assistants.

• Speech enhancement: reducing noise or improving quality of speech signals.

• Speech synthesis: generating human-like speech for applications like voice assistants.

• Speech compression: reducing the size of speech data for efficient storage and transmission.

Steps involved in A/D conversion

• Sampling: The continuous analog signal is sampled at regular intervals.

• Quantization: Each sample is assigned a digital value based on its amplitude.

• Encoding: The digital values are encoded into binary format for processing.

• Resolution: The number of bits used to represent each sample determines the resolution.

• Conversion: The final step involves converting the digital signal into an analog output.

The two types of Fast Fourier Transform (FFT) are Cooley-Tukey FFT and Radix-2 FFT.

• Cooley-Tukey FFT: Divides the DFT into smaller DFTs and recursively applies the algorithm.

• Radix-2 FFT: Decomposes the DFT into smaller DFTs of size 2, which are then combined to get the final result.

Types of digital filters include FIR filters, IIR filters, and adaptive filters.

• FIR filters: Finite Impulse Response filters have a finite impulse response, meaning they only respond to a finite duration input signal.

• IIR filters: Infinite Impulse Response filters have an infinite impulse response, allowing for feedback in the filter design.

• Adaptive filters: These filters adjust their parameters based on the input signal, making them suitable for changing environments.

• Examples...read more

DSP offers advantages such as higher precision, faster processing, and better noise reduction compared to ASP.

• DSP allows for higher precision in signal processing compared to ASP

• DSP can process signals faster than ASP due to specialized hardware and algorithms

• DSP techniques such as filtering and noise reduction are more effective than those in ASP

• DSP enables real-time processing of signals, which is crucial in applications like audio processing and telecommunications