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