Explore MATLAB source code curated for "Matlab" with clean implementations, documentation, and examples.
Recent research on various RNN architectures, inspired by Trask's blog demonstrating basic RNN implementation in Python, has been successfully ported to MATLAB with excellent experimental results. The implementation covers core RNN components including forward propagation, backpropagation through time (BPTT), and gradient computation.
This MATLAB implementation performs dimensionality reduction for M*N large datasets with clear procedural steps. The function y = pca(mixedsig) processes an n*T mixed signal matrix where n represents the number of signals and T denotes sampling points, returning an m*T principal component matrix. Algorithm workflow includes: 1) Mean centering, 2) Covariance matrix computation with eigenvalues/eigenvectors, 3) Threshold-based eigenvalue selection, 4) Descending eigenvalue sorting, 5) Small eigenvalue removal, 6) Large eigenvalue removal (typically skipped), 7) Selected eigenvalue merging, 8) Corresponding eigenvector selection, 9) Whitening matrix calculation, 10) Principal component extraction.
A comprehensive guide to solving the two-dimensional Poisson equation using MATLAB, including mesh generation, boundary condition specification, numerical solution techniques, and result visualization with code implementation details.
A MATLAB 2008a-based B-spline surface generation program featuring adjustable knot vectors and control points for customizable surface modeling, implementing fundamental B-spline algorithms for computational geometry applications.
This MATLAB M-file enables motor fault diagnosis by analyzing operational data to identify common failure types including rotor bar defects, stator winding shorts, and bearing faults through signal processing algorithms.
A MATLAB-based 2.5D forward modeling program for DC resistivity, designed for educational and reference purposes, featuring advanced numerical computation methods and comprehensive learning resources.
MATLAB-based spatial arc interpolation and simulation implementation, featuring independently developed M-file functions with standardized programming interfaces for enhanced usability in robotics and CNC applications
Missile trajectory simulation using MATLAB with modular modeling approach. The simulation enables analysis of missile performance characteristics and flight patterns. While step-by-step modeling is required to gain practical knowledge, MATLAB proves to be an efficient simulation tool among various available options. Key implementation aspects include modular system decomposition, differential equation solvers for trajectory calculation, and visualization functions for result analysis.
Implementation of 3D reconstruction based on binocular vision using MATLAB programming language, featuring comprehensive effect analysis and performance evaluation.
MATLAB-based implementation of robot path planning on a 2D plane using grid-based methods for environment and obstacle processing, featuring algorithm demonstrations and simulation capabilities.