Embedded Software and DSP Information

Hello, and welcome to the Embedded Software/DSP Information Page. This page is designed for engineering students and professionals in the work field interested in the field of Embedded Software and Digital Signal Processing. Below is a list of categories to choose from depending upon your choice of interest.

What is Section
What Is DSP Applications of DSP
What is Digital Filtering What is Discrete Fourier Transform
What is Fast Fourier Transform

C Code Section
Discrete Fourier Transform C code Fast Fourier Transform C code
Inverse Z Transform C code Remez Exchange Algorithm C code
Impulse Invariant C code FIR Design Using Windowing Method C code

Matlab Code Section
IIR Lowpass Filter simulation in Matlab IIR Bandpass Filter simulation in Matlab
IIR Highpass Filter simulation in Matlab IIR Bandstop Filter simulation in Matlab
IIR 3 Khz Lowpass Filter simulation in Matlab IIR 3.5 Khz Lowpass Filter simulation in Matlab
Simple Sine Wave simulation in Matlab with spectral plot FFT analysis function for plotting
Digital Oscillator Simulation White Noise Generation Simulation
ADPCM Simulation Program ADPCM simulation functon f()
ADPCM function sgn() Audio file for ADPCM simulation
ADPCM encode function ADPCM decode function
Image Lowpass Filter Simulation aero.pic input image
Display Image function Histogram Equalization Simulation
Histogram Equalization input image

Assembly Code Section
Initialization program for DSP56002EVM I/O audio Main Program 56002EVM
I/O audio loadable image 56002EVM I/O audio loadable image for 56307EVM
Initialization routine for 56307EVM board I/O Main Program for 56307 EVM board
Main program for white noise generation 56307 White noise generation routine 56307

What Is Embedded Software

What Is DSP

DSP, digital signal processing, is the science of taking the digital representation of signals and using digital processors to analyze, modify, or extract information from those signals. Most signals in nature are analog in form. This means that they are continuous in time and represent the variations of some physical quantity such as sound, or electromagnetic waves. To process such physical continuous quantities; we need to sample this analog signal at regular intervals and represent these samples in a digital form thus creating the digital signal. The advantages of digital signal processing compared to analog processing are:
  1. We can reproduce identical performance from unit to unit. Since the signal is in digital form; we are not suceptable to variations such as temperature and age.
  2. Because of the use of microprocessors; we can introduce functions such as delay which would be extremely difficult in the analog world; thus providing much greater flexability in creating features such as voice storage; or electronic shock protection used in portable car CD players.
  3. Superior Performance - DSP can be used to perform functions not possible with analog signal processing. For exampl, linear phase response can be achieved , and complex adaptive filtering algorithms can be implemented using DSP techniques.
  4. Guaranteed Accuracy - Accuracy is only determined by the number of bits used.
  5. Size of product- Now with the explosive growth in semiconductor technology the product using DSP technology can be implemented inside chips; thus reducing the size of the product thus reducing cost.
Applications of DSP

DSP is one of the fastest growing fields in modern electronics being used in any area where information is handled in a digital form or controlled by a digital processor. Application areas include the following.