Chaos-Enhanced Particle Swarm Optimization for Image Thresholding
Chaos-enhanced particle swarm optimization (CPSO) improves standard PSO by integrating deterministic chaos to diversify the search space and escape premature convergence. In image thresholding, CPSO optimizes scalar or multi-level thresholds by maximizing separability between foreground and background regions—typically using histogram-based cri ...
Posted on Mon, 18 May 2026 01:39:05 +0000 by FramezArt
Comprehensive MATLAB Plotting Techniques
2D Line Plot
Displays the relationship between two variables
clear; % Clear all variables from the workspace
clc; % Clear the command window
close all; % Close all figure windows
x = linspace(1,200,100); % Generate 100 evenly spaced values between 1 and 200
y1 = log(x) + 1; % C ...
Posted on Sun, 17 May 2026 01:12:56 +0000 by edcellgavin
Generating Cylindrical and Conical Surfaces with MATLAB's cylinder Function
The cylinder function in MATLAB generates coordinate data representing the surface of a cylinder. These coordinates are essential for creating three-dimensional visualizations using functions like surf or mesh.
Function Syntax and Behavior
The cylinder function produces x, y, and z coordinates for a unit cylinder. By default, it creates a cylin ...
Posted on Fri, 15 May 2026 19:35:57 +0000 by weekenthe9
Implementation of the Lucas-Kanade Pyramid Optical Flow Method in MATLAB
MATLAB Function for Pyramid-Based LK Optical Flow
This article presents a complete MATLAB implementation of the Lucas-Kanade (LK) optical flow algorithm using a pyramidal (coarse-to-fine) approach. The function estimates the apparent motion vector field between two successive grayscale image frames.
Main Algorithm Function
function [flowX, flow ...
Posted on Fri, 15 May 2026 12:24:19 +0000 by Brandito520
Essential MATLAB Operations
Core MATLAB Syntax
MATLAB primarily utilizes .m files for script execution. The development environment features workspace (left), editor (right), and output (bottom-right) panes.
Basic Input and Output
radius = input('Enter circle radius: ');
area = pi * radius^2;
fprintf('Area = %.2f\n', area);
This script calculates circle area using input ...
Posted on Fri, 15 May 2026 11:15:03 +0000 by sincejan63
Techniques for Analyzing Signal Correlation and Alignment
Normalizing Sampling Frequencies
In signal processing appplications, it is frequently necessary to compare data sets that possess different sampling rates or durations. For instance, matching a live audio stream against a database of stored templates requires normalization, as stored data is often downsampled to conserve memory. Direct subtract ...
Posted on Fri, 15 May 2026 01:29:44 +0000 by kamurj
Image Edge Detection Using Wavelet Transform
Edge detection is a fundamental technique in digital image processing, designed to isolate the boundaries of objects within a scene. These boundaries typically correspond to regions where significant fluctuations in pixel intensity or color occur, providing critical information for object recognition, structural analysis, and texture categoriza ...
Posted on Fri, 15 May 2026 00:47:35 +0000 by waynewex
Sharing Data Across MATLAB Callback Functions
Managing Application State in UI Components
Callback functions define UI component behavior in MATLAB applications. When components have interdependencies, callbacks often require access to data defined in the main application function or need to exchange information with other callbacks. Since each calback operates in its own scope, explicit d ...
Posted on Thu, 14 May 2026 22:23:47 +0000 by AcidCool19
Wavelet-Based Feature Extraction for Mechanical Vibration Signals Using MATLAB
1. Methodology Overview
The wavelet feature extraction pipeline for mechanical vibration signals follows a multi-scale decomposition → feature quantification → feature fusion workflow, consisting of these core stages:
Wavelet Decomposition: Multi-level decomposition to capture frequency band characteristics
Time-Frequency Analysis: Extraction ...
Posted on Sat, 09 May 2026 11:53:24 +0000 by mysoogal
Building and Forecasting with ARIMA Models in MATLAB: A Practical Guide
Start by loading the data from an Excel file named data.xlsx containing a single numeric column Value. The code splits the series into an 80% training segment and reserves the remainder for testing.
% Clear workspace and figures
clc; clear; close all;
% Control parameters
forceManual = 1; % 1 = use fixed ARIMA(2,1,1); 0 = auto-order selec ...
Posted on Fri, 08 May 2026 02:06:49 +0000 by juschillinnow