Introduction to Digital Signal Processing: Concepts and Applications
This course provides a comprehensive introduction to Digital Signal Processing (DSP), focusing on the fundamentals of discrete-time signals and systems. Students will learn to differentiate between continuous and discrete-time signals, explore applications in speech and image processing, and understand the conversion of analog signals to digital sequences. The course outlines the DSP components and discusses techniques like frequency selective filtering and echo cancellation, highlighting their significance in real-time applications. Gain insights into DSP system design and implementation with practical computation examples.
Introduction to Digital Signal Processing: Concepts and Applications
E N D
Presentation Transcript
DIGITAL SIGNAL PROCESSING Introduction
Discrete Time signal • Sequence x[n] as opposed to continuous time signals x(t)
Discrete in Nature • Population statistics • Stock market indices
Sampled continuos time (analog) signals • Example • Speech
Speech Processing Original speech High pass Down sample Up sample Low pass
Video Processing General Concept: Object 1 Motion Analysis Object 2 Video Synthesis Applications Analysis
Discrete-Time System y(n)=T{x(n)}
Why DTSP? • Discrete Time Signal Processing of Continuous Signals x (n) y (n) y(t) x (t)
WhyDTSP? Digital Signal Processing (DSP) is derived from DTSP y(n) y(n) x(t) x(n)
DSP COMPONENTS • Converting analog signal into digital sequence. • Performing all signal processing operations in digital in digital form. • If necessary converting the digital information back to analog signal. • A TYPICAL DSP SCHEME Analog Filter ADC DSP Processor DAC Analog Filter
Comparison of Chips POWE R CONSUMP T I ON FLEXIBILITY
Course Outline • DSP: A/D,D/A • System Design and Implementation • Practical computation of F