Signal Processing Toolbox
Description
- Introduction and Key Features
- Generating, Visualizing, and Analyzing Signals
- Performing Spectral Analysis in MATLAB
- Designing Digital FIR and IIR Filters
- Developing Signal Processing Algorithms
Introduction
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.
Key Features
- Signal and linear system models
- Waveform and pulse generation functions, including sine, square, sawtooth, and Gaussian pulse
- Statistical signal processing 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
- Signal transforms, including fast Fourier transform (FFT), discrete Fourier transform (DFT), and short-time Fourier transform (STFT)
- Linear prediction and parametric time-series modeling
