Professional MATLAB source code with comprehensive documentation and examples
Simulation of power distribution patterns at both transmitter and receiver ends in visible light communication systems, with code implementation insights.
Wavelet Threshold Denoising: A Time-Scale (Time-Frequency) Signal Analysis Approach for Noise Reduction Applications
Simulation of special light field phases and specialized light field intensity distribution arrays, demonstrating optical field modeling techniques using numerical computation methods.
Comprehensive analysis of EMG signal processing techniques featuring time-domain and frequency-domain feature extraction including Root Mean Square (RMS), Median Frequency (MDF), and Mean Power Frequency (MPF) with implementation insights
MATLAB code implementation for APSK (Amplitude and Phase Shift Keying) demodulator with detailed signal processing methodology
Digital Down Conversion (DDC) Implementation Using Quadrature Sampling and Low-Pass Filtering Techniques for Single-Frequency and BPSK Signal Processing
Analysis of non-stationary signals featuring Short-Time Fourier Transform (STFT), Gabor Expansion, Choi-Williams Distribution, and Wigner-Ville Distribution with MATLAB implementations.
The Gabor filter is renowned for approximating the receptive field properties of the visual cortex in human vision systems. Recent advancements in computer vision applications demonstrate the technique's proven success and promising potential. This d
PADDEDSIZE calculates computationally efficient padded array dimensions optimized for FFT-based filtering implementations, ensuring proper frequency domain alignment between input data and filter kernels.
Empirical Mode Decomposition (EMD) is an adaptive signal decomposition method primarily applied to nonlinear and non-stationary signals. Ensemble Empirical Mode Decomposition (EEMD) addresses the mode mixing problem inherent in standard EMD. Implemen
Implementing wavelet analysis techniques to detect and diagnose faults in induction machines with signal processing algorithms and MATLAB code examples.
MUSIC algorithm for spatial spectrum estimation and DOA (Direction of Arrival) analysis: A power spectrum estimation method based on matrix eigenvalue decomposition comprising two non-parametric estimation approaches - eigenvector estimation and MUSI
This demonstration showcases the implementation of adaptive filtering techniques for acoustic noise attenuation through active noise control, featuring real-time algorithm adaptation and anti-noise signal generation.
ECG Signal Preprocessing Implementation: 50Hz frequency filtering for noise removal, baseline wander correction for signal stabilization, and graphical plotting for analysis including MATLAB code approaches and algorithm explanations.
This project implements frequency estimation of sinusoidal signals embedded in Gaussian white noise through three high-resolution spectral estimation methods: Pisarenko Harmonic Decomposition, MUSIC (Multiple Signal Classification) algorithm, and ESP
The Hilbert-Huang Transform (HHT) represents an innovative approach for analyzing non-stationary signals, combining Empirical Mode Decomposition (EMD) with Hilbert spectral analysis. In implementation, signals undergo EMD processing to decompose them
FIR Filter Design (Finite Impulse Response Filter Implementation) featuring MATLAB source code for 12 distinct FIR design methods, including ideal bandpass filter impulse response calculation, Modified Bessel function implementation, Kaiser window pa
(1) Implement a Canny edge detector function using MATLAB (or C) with Gaussian filtering capabilities; (2) Apply this custom function to detect edges in images corrupted by salt-and-pepper or Gaussian noise; (3) Utilize MATLAB's built-in Canny edge d
This MATLAB-based toolkit provides comprehensive ECG signal processing capabilities including noise reduction preprocessing, data normalization, high/low-frequency notch filters, and ECG signal simulation algorithms. It contains both executable code
Implementation of frequency estimation for three sinusoidal signals with additive white Gaussian noise using Pisarenko harmonic estimation, MUSIC algorithm, and ESPRIT algorithm. The attached code provides MATLAB implementations with detailed explana