MATLAB Implementation of Voice Signal Extraction and Recognition
Voice extraction and recognition system implementing fundamental frequency extraction and analysis from speech signals using signal processing techniques
MATLAB Time-Frequency Analysis Toolbox
MATLAB's Time-Frequency Analysis Toolbox designed to facilitate comprehensive signal analysis with advanced implementation techniques and key algorithm support.
MATLAB Implementation of HHT (Hilbert-Huang Transform) for Signal Analysis
HHT (Hilbert-Huang Transform) employs Empirical Mode Decomposition to break down signals into intrinsic mode functions for advanced signal processing and time-frequency analysis.
MATLAB Implementation of Wavelet Analysis
Wavelet analysis and wavelet energy spectrum analysis techniques for signal processing and analysis. Implementation covers signal decomposition, frequency-energy characterization, and practical MATLAB applications using wavelet toolbox functions.
MATLAB Implementation for Computing Signal Instantaneous Frequency
MATLAB-based computation of signal instantaneous frequency for advanced signal analysis applications
Wavelet Packet Transform for Signal Analysis
MATLAB implementation of wavelet packet transform for signal analysis and denoising, featuring complete wavelet decomposition and reconstruction procedures with detailed algorithmic explanations
Wavelet Packet Transform for Signal Analysis
A comprehensive MATLAB application utilizing wavelet packet transform to extract feature vectors and frequency component power spectra from two signals, with detailed algorithm implementation and function descriptions
MATLAB Program for Signal Analysis Using Wavelet Packet Transform
MATLAB implementation for signal analysis using wavelet packet transform with detailed code descriptions and algorithm explanations
Analysis and Visualization of Ambiguity Functions for Various Signal Types
This source code implements comprehensive ambiguity function analysis and plotting capabilities for multiple signal types, including tested implementations for Barker codes, linear frequency modulated (LFM) signals, and pulse signals with configurable parameters.
C-Means Clustering BP Neural Network Signal Analysis and Processing Method
C-means clustering BP neural network signal analysis and processing method for training and optimizing simulated data samples to enhance accuracy and performance, featuring implementation details of clustering algorithms and neural network training techniques.