Signal Analysis Curriculum

# Signal Analysis Curriculum Design

You are an electrical engineering professor and curriculum developer with expertise in signal processing, communications, and applied mathematics. Design a complete signal analysis curriculum.

## Curriculum Parameters
- **Target audience:** [AUDIENCE] (undergraduate EE students, graduate students, working engineers upskilling, bootcamp learners)
- **Duration:** [DURATION] (semester course, 8-week intensive, self-paced)
- **Prerequisites assumed:** [PREREQUISITES] (calculus, linear algebra, basic circuits, programming)
- **Focus area:** [FOCUS] (continuous-time signals, discrete/digital, communications, audio, biomedical, radar/RF)
- **Tools to use:** [TOOLS] (MATLAB, Python/NumPy/SciPy, GNU Radio, Octave)

## Signal Analysis Curriculum

### Module 1: Foundations of Signals and Systems
- Signal classification: deterministic vs. random, continuous vs. discrete, periodic vs. aperiodic
- Basic signal operations: time shift, scaling, reversal, addition
- Elementary signals: impulse, step, ramp, sinusoid, complex exponential
- System properties: linearity, time-invariance, causality, stability
- Convolution: graphical and analytical methods

### Module 2: Continuous-Time Frequency Analysis
- Fourier Series: derivation, coefficients, convergence, symmetry properties
- Fourier Transform: definition, properties (linearity, duality, convolution theorem)
- LTI systems: frequency response and Bode plots
- Ideal filters: lowpass, highpass, bandpass concepts

### Module 3: Laplace and Z-Transforms
- Laplace Transform: definition, ROC, properties, inverse
- Transfer functions and poles/zeros
- Z-Transform: definition, ROC, relationship to DTFT
- Discrete-time system analysis with Z-Transform

### Module 4: Discrete-Time Signal Processing
- Sampling theorem: Nyquist rate, aliasing, anti-aliasing filters
- DTFT and DFT: relationship and properties
- Fast Fourier Transform (FFT): algorithm, efficiency, applications
- Digital filter design: FIR vs. IIR, windowed sinc, Butterworth, Chebyshev

### Module 5: Applied Signal Analysis
- Spectral analysis: power spectral density, periodogram, Welch method
- Short-Time Fourier Transform (STFT) and spectrograms
- Wavelet transforms: introduction and use cases
- Applications in [FOCUS]: practical examples with [TOOLS]

### Module 6: Practical Labs & Projects
- Lab assignments using [TOOLS]: signal generation, filter design, spectral analysis
- Capstone project options for [AUDIENCE]
- Assessment methods: problem sets, lab reports, oral examination

### Learning Resources
- Recommended textbooks: Oppenheim & Schafer, Proakis & Manolakis, Haykin
- Online resources and datasets
- Software setup guide for [TOOLS]

Provide a week-by-week schedule for [DURATION] tailored to [AUDIENCE].