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Electrical Engineering - ELEN 304

Networks II

• Define the following systems characteristics: causal systems, lumped constant and distributed parameter systems, deterministic and stochastic systems, linear and nonlinear systems, time invariant and time varying systems, and continuous time and discrete time systems.
• Calculate the average and RMS values of a signal of arbitrary waveform.
• Calculate the power in a complex waveform.
• Calculate decibel levels for power, voltage, and/or current.
• Use the Fourier Transform to compute the frequency domain description for a time domain energy waveform.
• Use the Fourier Series to compute the frequency domain description for a time domain power waveform.
• Demonstrate the duality between the pulse shape in one domain (time or frequency) and the sinc(x) shape in the other domain (frequency or time).
• Use the Fourier Transform for calculating the spectrum of a signal.
• Use the impulse (delta) function in signals and systems.
• Convolution of two signals in the time domain or two signals in the frequency domain.
• Use convolution to compute the spectrum of a signal when the signal is composed of the product of two other signals, e. g. AM signals, windowed data samples, etc.
• Sample a continuous waveform such that all information in the continuous waveform is contained in the sampled values.
• Calculate sampling rate to reduce aliasing to a specified level.
• Calculate sampling rate and word size for digital music.
• Calculate z-transform of a digital signal.
• Calculate frequency content of a digital signal described in the z domain.
• Solve difference equations using classical techniques. 
• Solve difference equations using z-transforms.
• Inverse transformation of a z-domain transfer function into the time domain using direct division or partial fraction expansion.
• Convert a z-domain system description to a difference equation for developing a computer algorithm.
• Design a low pass filter algorithm in the continuous domain using Butterworth or Chebychev polynomials.
• Design band-pass, high-pass, and notch filters by transforming the corresponding low pass filter transfer function.
• Design a computer algorithm to implement Butterworth and Chebychev filters on digital signals.
• Design a signal processing system to filter raw signals (e. g. heartbeats) and determine significant information contained in these signals.
• Use Matlab to provide the computational work in signal processing.
• Develop m-files in Matlab to implement signal processing algorithms.
• Convert a system into state variables.
• Use Matlab to convert the transfer description of a system to a state space description.

Prepared by Dr. Therrill Valentine