A Practical Introduction to Digital Signal Processing (DSP) for dsPIC developers

Overview
To take advantage of the DSP capabilities of the dsPIC architecture a sound understanding of the principles and practice of Digital Signal Processing is Required. This 5 day course avoids digging deep into the underlying theory and maths. Rather it aims to provide a sound understanding of the principles, uses and limitations of Digital Signal Processing. Its goal is to ensure that engineers learn how to select and parameterize the most appropriate DSP Algorithms for the task at hand.

Key Skills
After attending this course you will:

• Understand the uses and limitations of DSP
• Know those features of the dsPIC architecture relevant to DSP
• Be able to design and implement DSP filters on a dsPIC
• Be able to perform frequency analysis of signals using the Fast Fourier Transform on the dsPIC

Course Contents
Overview of DSP What can DSP do

• DSP vs. analog electronics
• DSP and microcontrollers
• DSP and the dsPIC
• Limitations of DSP

Analog Signals and Systems

• frequency and time description of signals and systems
• linear and time invariant systems

Analog Filters

• uses and purpose
• ideal vs. real world
• filter specification
  • filter types (low pass, highpass, bandpass, ....)
  • specifying filters (magnitude response, phase response, transient response)
• passive vs. active filters
• poles and zeros

Overview of Concepts Underlying Discrete-Time Signals and Systems

• time and frequency domain description of discrete-time signals
• quantization (linear, non-linear, noise)
• A-to-D and D-to-A conversion
• overview of digital filters - FIR and IIR

FIR Filters

• understanding convolution
• how FIR filters work
• generating coefficients for FIR filters (Parks-McClellan, Windowing, Frequency Sampling)

IIR Filters

• basic concepts
• design techniques (manual, time-domain methods, frequency domain methods)
• cascade and parallel IIR filter structures

Implementing filters on a dsPIC

• dsPIC as a DSP Processor
• dsPIC compared with TI DSP processors
• overview of programming the dsPIC in 'C' and Assembler
  • data representation issues, speed vs. size optimization ...
  • finite word length effects (coefficient quantization, limit cycles)

Frequency Analysis

• Discrete Fourier Transform (DFT)
• Fast Fourier Transform (FFT)
• implementing FFT on the dsPIC
• inverse DFT/FFT
• overview of wavelets

Correlation

• cross-correlation
• auto-correlation
• pseudo-noise signals
• signal averaging

Sampling

• choosing sampling rates
• multi-rate signal processing
• decimation
• interpolation

Signal Synthesis

• random numbers - generating pseudo random numbers
• functions - polynomials, sine, cosine, arbitrary waveforms ...