2D Fourier Transform for Image Recognition and Processing in Julia

An exploration of using the 2D Fast Fourier Transform (FFT) in Julia to analyze image frequencies, understanding how computers extract features for recognition.

An exploration of using the 2D Fast Fourier Transform (FFT) in Julia to analyze image frequencies, understanding how computers extract features for recognition.

Using Julia's FFT Fast Fourier Transform to analyze the periodicity of sunspot activity and discover the famous 11-year solar cycle.

A tutorial on using the Fast Fourier Transform (FFT) in Julia to analyze the frequency spectrum of blue whale vocalizations and tiger roars.

A comprehensive guide to the Fourier Transform, covering its mathematical foundations, the relationship between time and frequency domains, and practical implementations in Julia. Includes examples of spectral analysis, Gaussian pulses, cosine waves, and the Gibbs phenomenon when building square waves from harmonics.

A comprehensive guide to damping in mechanical systems. Learn about viscous, structural, and Coulomb damping, damping estimation methods, and compare Python analytical solutions with COMSOL multiphysics simulations.

Learn how to locate damage in structures using sound waves. This article explains the physics of acoustic emission, the mathematics of TDOA localization, and provides complete MATLAB code—from theory to working implementation.

A comprehensive guide to Brillouin zones: from reciprocal space construction to high-symmetry point analysis. Learn to navigate band structure diagrams for phononic crystals and acoustic metamaterials.

A comprehensive guide to acoustic dispersion curves: from basic definitions to practical applications in NDT and metamaterials. Learn to read ω-k diagrams, understand phase vs. group velocity, and interpret Lamb wave and phononic crystal spectra.

This post demonstrates end-to-end implementation of local large language models using Ollama framework, featuring three open-source clients: Page Assist browser extension for web integration, Cherry Studio for VS Code development environments, and AnythingLLM desktop application for document-driven AI workflows. The tutorial covers installation protocols, API configuration best practices, and performance optimization techniques for Windows-based LLM deployments.

Want to run LLMs locally on Windows? This guide walks you through the complete Ollama workflow—from installation and path configuration to model selection—getting your private AI up and running in minutes.