Basic SIGNAL PROCESSING with MATLAB

MATLAB Signal Processing Toolbox provides industry-standard algorithms for analog and digital signal processing (DSP). You can use the toolbox to visualize signals in time and frequency domains, compute FFTs for spectral analysis, design FIR and IIR filters, and implement convolution, modulation, resampling, and other signal processing techniques. Algorithms in the toolbox can be used as a basis for developing custom algorithms for audio and speech processing, instrumentation, and baseband wireless communications.

The more important features are the following:

• Signal and linear system models
• Signal transforms, including fast Fourier transform (FFT), discrete Fourier transform (DFT), and short-time Fourier transform (STFT)
• Waveform and pulse generation functions, including sine, square, sawtooth, and Gaussian pulse
• Transition metrics, pulse metrics, and state-level estimation functions for bilevel waveforms
• Statistical signal measurements and data windowing functions
• Power spectral density estimation algorithms, including periodogram, Welch, and Yule-Walker
• Digital FIR and IIR filter design, analysis, and implementation methods
• Analog filter design methods, including Butterworth, Chebyshev, and Bessel
• Linear prediction and parametric time-series modeling