MATLAB Implementation of BP Algorithm with Basis Pursuit Reconstruction
BP Algorithm - Basis Pursuit Reconstruction Algorithm Based on Compressive Sensing, Effectively Reconstructing Original Signals with Code Implementation Details
One-Dimensional Signal Denoising Using Modulus Maximum Algorithm
This program implements modulus maximum algorithm for 1D signal denoising with classical alternating projection method for signal reconstruction.
Signal Reconstruction Using Matching Pursuit (MP) Algorithm
MATLAB implementation of the MP algorithm for signal reconstruction with detailed code comments and algorithm explanation
Spectral Analysis of Wavelet Filters
Implementation of wavelet filter spectral analysis using Mallat decomposition algorithm for signal reconstruction
Signal Reconstruction Using Orthogonal Matching Pursuit (OMP) Algorithm Implementation
Signal Reconstruction via Orthogonal Matching Pursuit (OMP) Algorithm with Code Implementation Insights
Beamforming: Techniques and Implementations for Source Signal Reconstruction from Sensor Arrays
Beamforming is the process of reconstructing a source signal from a sensor array through two primary approaches: (1) amplifying the contributions from desired sources and (2) suppressing interfering signals. Classical beamforming requires prior knowledge of the direction of arrival (DOA) of the target signal. Blind beamforming attempts to recover the source signal without DOA information, employing statistical or optimization-based methods. The core principle involves applying weighted summation to array element outputs, "steering" the antenna beam toward a specific direction to maximize the output power of the desired signal—this optimal steering angle provides the DOA estimate. Although individual antenna elements have omnidirectional radiation patterns, weighted combination of their outputs concentrates gain in a specific direction, effectively forming a directional "beam."
Principal Component Analysis: Extracting Key Features for Signal Reconstruction
Comprehensive Introduction to Principal Component Analysis (PCA) - Methods for Extracting Dominant Features and Reconstructing Original Signals with Code Implementation Insights
Mallat Algorithm Implementation for Signal Decomposition and Reconstruction
Implementation of signal decomposition and reconstruction using Mallat algorithm, demonstrating wavelet transform operations through filter banks and reconstruction techniques
Compressive Sensing DOA Reconstruction Algorithm: Orthogonal Matching Pursuit (OMP)
Application of Orthogonal Matching Pursuit (OMP) in Compressive Sensing for Direction of Arrival (DOA) Estimation