Research and Simulation of Image Segmentation Algorithms Based on MATLAB
Research and Simulation of Image Segmentation Algorithms Using MATLAB with Implementation Techniques and Performance Analysis
Explore MATLAB source code curated for "研究" with clean implementations, documentation, and examples.
Research and Simulation of Image Segmentation Algorithms Using MATLAB with Implementation Techniques and Performance Analysis
Research and implementation of adaptive beamforming algorithms for smart antennas, featuring improvements to fundamental algorithms and computational methods, with code implementation insights for enhanced learning and practical applications.
A comprehensive utility package for Differential Evolution Algorithm, designed for researchers and learners interested in studying DE implementation methodologies and optimization techniques
A useful research tool for ultrasonic systems that generates customizable acoustic field simulations through parametric inputs, enabling algorithm validation and acoustic image analysis.
Multi-level LDPC Extended Min-Sum Decoding (EMS) has achieved successful implementation and is expected to provide valuable assistance for researchers in future studies
MATLAB-based GPS receiver implementation code with detailed algorithms for signal acquisition, tracking, and synchronization processes, featuring practical implementation approaches for GPS signal processing.
A complete repository of Independent Component Analysis (ICA) source codes, featuring extensive algorithm implementations with detailed explanations to support beginners in their research and study
Self-developed iris and pupil segmentation algorithm implemented during thesis research, utilizing binarization techniques with accompanying sample images. Seeking research collaboration in this field.
The fractional-order unified chaotic system synchronization program facilitates synchronization of fractional-order chaotic systems and is particularly valuable for research in fractional-order dynamics, featuring implementation of synchronization algorithms and numerical computation methods.
Deconvolution and signal restoration represent theoretically challenging branches in signal processing technology. Due to their extensive applications, they remain hot research topics. Relevant research reports are scattered across various professional academic journals and books, yet there exists a notable gap for students and researchers seeking a systematic guide reflecting recent developments. This book aims to fill this void by systematically organizing fundamental concepts, highlighting key advancements, challenges, and future directions. The text emphasizes the physical origins of deconvolution problems, theoretical methodologies' core principles, application scopes, and limitations. It incorporates practical code examples, algorithm implementations, and real-world datasets to facilitate hands-on application, while providing comprehensive theoretical foundations and cutting-edge developments for advanced research.