ECET 33900 - Digital Signal Processing
Credit Hours: 3.00.
The course introduces students to the fundamental principles associated with processing discrete time signals. The architecture, instruction set and hardware and software development tools associated with a fixed point general purpose VLSI digital signal processor are examined. Some common real-time applications are implemented such as digital filters and DFT-based spectral estimation on a typical fixed point digital signal processor.
1. Describe the architectural features of a DSP and relate these to the DSP kernel equation.
2. Manipulate different binary number formats associated with a fixed point DSP.
3. Develop and debug simple programs that involve SOPs, modulo addressing, scaling and extraction of result, and common DSP program structures.
4. Describe the consequences and limitations of sampling baseband signals including the Nyquist rate and bandwidth, quantization noise, aliasing, frequency folding, reconstruction, spectrum of sampled baseband signals.
5. Express a sampled deterministic analog signal in closed mathematical form and expanded form using the unit sample.
6. Express a sampled signal in terms of the Z transform, in expanded and closed form.
7. Describe the relationship between the transfer function and impulse response in an LTI system.
8. Describe the operation of convolution and its implementation using hand calculations, mathematical software packages, and a fixed-point DSP.
9. Design and analyze FIR filters with the aid of a mathematical software package such as MATLAB.
ECET 27900 Minimum Grade of D- and
(MA 22200 Minimum Grade of D- or
MA 22800 Minimum Grade of D- or
MA 22400 Minimum Grade of D- or
MA 16200 Minimum Grade of D- or
MA 16600 Minimum Grade of D- or
MA 23000 Minimum Grade of D- or
MATH M1200 Minimum Grade of D- or
MATH M2090 Minimum Grade of D- or
MATH M2160 Minimum Grade of D-)
Must be enrolled in Electrical Engineering Technology