Digital Signal Processing, DSP Electrical Engineering Study Course

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Introduction to Digital Signal Processing

Applications of DSP

Digital vs. Analog

Discrete vs. Continuous

Introduction to Probability

Continuous and Discrete Signal Definition

Mean and Standard Deviation

Average Deviation

RMS, Root-Mean-Square

Signal to Noise

Coefficient of Variation

Signals and Processes

Acquired Signal

Statistical Irregularity

Variation, Fluctuation, Noise

Probability Mass Function, PMF

Probability Density Function, PDF

Normal Distribution

Precision and Accuracy

Analog to Digital Converter, A/D

Digital to Analog Converter, D/A

A/D Converter Resolution

Sampling Theorem

Nyquist Theorem

Anti-Aliasing Filters

Low-Pass Sampling

Band-Pass Sampling

Linearity Requirements

Discrete System

Impulse Response

Input and Output Side Algorithm

Properties of Convolution

Common Impulse Response

Discrete Derivative

Casual and Non-Casual Signals

Mathematical Properties

Input and Output Transference

Central Limit Theorem

The Discrete Fourier Transform, DFT

Continuous Equation

Discrete Equation

Rectangular Form

Exponential Form

Notation and Format

Frequency Domain

Calculating the DFT

Digital Filters

Finite Impulse Response Filters, FIR Filter

Structure of a FIR Filter

FIR Filter Equation Form

Using Convolution in a FIR Filter

FIR Filter's Impulse Response

Low-Pass FIR Filter

High-Pass FIR Filter

Band-Pass FIR Filter

Band-Reject FIR Filter

Infinite Impulse Response Filter, IIR Filter

Structure of an IRR Filter

IRR Filter Equation Form

Digital Filtering

Moving Average Filter

Realization by Convolution

IRR Filter Noise Reduction

IRR Filter of Recursive Implementation

Windowed Sinc Filters

Sinc Function and Response Characteristics

Introduction to Z-Transforms

Relationship between Z-Transform and LaPlace Transform

S-Plane Transform

Z-Plane Transform

Z-Transform Format

Unit Distance Circle

Z-Transform Transfer Equations

Digital Signal Processing

An introduction to the topic of Digital Signal Processing (DSP) by preparing students to have an understanding of the roll of DSP in electronic systems design and develop a foundation for further study in DSP. Analysis of discrete systems and signals, introduction to probability, discrete signals, sampling, linear systems, introduction to convolution and correlation, discrete Fourier transforms, digital filtering, and z-transforms. Fundamentals of digital communication systems are initially introduce in Telecommunications II.

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