Course Design Simulation for Industrial Robots
Simulation program for industrial robot course design, primarily implementing Lagrange Equation method and Jacobian method with kinematic and dynamic modeling approaches
Course Design for Principles of Automatic Control
Course design for Principles of Automatic Control featuring MATLAB programming and simulation examples including root locus analysis, time-domain analysis, frequency-domain analysis, and control system design and compensation techniques.
VQ-Based Speaker Recognition System Implementation
Course Design Requirements and Objectives Speech recognition represents a critical component in human-computer interface design and serves as a vital application technology in speech signal processing. Vector Quantization (VQ) has demonstrated excellent performance in isolated word recognition systems, particularly through Finite-State Vector Quantization (FSVQ) techniques that significantly enhance recognition accuracy. VQ-based isolated word recognition systems offer superior comprehensive characteristics including high classification accuracy, minimal storage requirements, and real-time response capabilities. This course project requires designing a speaker-dependent isolated word recognition system using VQ methodology. Utilizing MATLAB tools, students will develop VQ codebook training programs and recognition algorithms to identify specific voice commands such as "Up," "Down," "Left," and "Right." Key implementation components include: 1. Designing a speaker-dependent isolated word recognition system based on VQ technology, encompassing voice acquisition and recognition detection experiments 2. Developing MATLAB simulation programs with system modulation and performance analysis 3. Implementing feature extraction algorithms (e.g., MFCC) and VQ codebook generation using LBG algorithm 4. Creating pattern matching mechanisms through distance calculation functions like Euclidean distance measurement
IIR Butterworth Low-Pass Filter Design
Design of IIR Butterworth Low-Pass Filters - A Course Project for Digital Signal Processing Students, Featuring Algorithm Implementation and MATLAB Code Examples
Voice Signal Analysis and Processing Course Design with MATLAB Implementation
MATLAB-based course design for voice signal analysis and processing involving recording personal voice signals, signal sampling, time-domain waveform and spectrogram plotting, filter design using window function method or bilinear transformation with frequency response visualization, signal filtering using custom-designed filters, comparative analysis of pre/post-filtering signals, and audio playback with code implementation details.
Digital Signal Processing: Design of Various Filters
Digital Signal Processing: Design of Various Filters - Complete source code and lab reports from the junior-year course project in Electronic Information Engineering at Central South University. Features implementations of FIR/IIR filters, windowing techniques, frequency response analysis, and filter design algorithms. Available for download!
PSK Modulation and Demodulation with Noise Addition
PSK modulation and demodulation with noise addition - a communication principles course project focusing on digital signal processing implementation.
Levinson Algorithm Implementation for Power Spectrum Estimation
Course project implementing Levinson algorithm for power spectrum estimation, including detailed experimental documentation with code analysis and performance evaluation.
Image Processing Applications Developed Using MATLAB or VC Languages
Source code for image processing applications developed using MATLAB or VC languages, suitable for course projects with enhanced algorithm descriptions and implementation approaches.
MATLAB Code Implementation of Kalman Filter with Custom Function
MATLAB source code for Kalman Filter implementation with function signature: [Y, PY, KC] = myKalman(x, A, B, Q, H, R, y0, P0). This implementation features a complete Kalman filtering algorithm developed for academic coursework, including state prediction, measurement update, and covariance matrix handling.