Explore MATLAB source code curated for "研究" with clean implementations, documentation, and examples.
Investigation of OFDM system anti-interference techniques using MATLAB simulation environment, evaluating performance metrics including bit error rate (BER) and frame error rate (FER) for CP-equalized OFDM systems under multipath and fading channel conditions, with implementation analysis of key algorithms.
This MATLAB implementation demonstrates the immune clonal algorithm, an emerging and effective optimization technique that has gained significant research attention in recent years. The program includes key components such as antibody initialization, affinity calculation, clonal selection, and mutation operations.
This algorithm is designed for precise measurement of small displacements and bridge deformations, featuring robust matching techniques and high-precision computational methods that provide valuable references for pattern matching research. Contact: QQ526289
The Kalman Filter Development Kit (MATLAB Version) contains numerous well-crafted functions and utilities with powerful capabilities, making it an excellent resource for researchers working on filtering algorithms. The toolkit implements essential Kalman filtering operations including state prediction, measurement update, covariance matrix handling, and noise parameter configuration.
This is a MIMO channel modeling program platform designed to facilitate research in channel modeling, featuring configurable simulation parameters and realistic propagation environment implementations
MATLAB source code for studying power adaptive allocation algorithms in OFDM systems (generates bit error rate plots for performance evaluation)
Research and Implementation of Content Authentication Semi-Fragile Watermarking Algorithm. This program implements image semi-fragile watermarking using a DCT-based approach, featuring adaptive embedding strategies and tamper detection mechanisms. Particularly suitable for researchers studying semi-fragile watermarking techniques.
This source code implements blind image deblurring algorithms, which represent one of the most actively researched approaches in image deblurring methodologies, featuring implementations of kernel estimation and non-blind restoration techniques.
MATLAB-based stereo vision calibration program suitable for image registration studies, implementing camera parameter estimation and 3D reconstruction algorithms
This research focuses on the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Modified Adaptive Unscented Kalman Filter (MAUKF), investigating the fundamental principles and distinctive characteristics of each algorithm. The EKF linearizes the Kalman Filter locally, featuring simple implementation with low computational complexity, suitable for weakly nonlinear Gaussian environments. The UKF approximates the posterior probability density of the state using a set of deterministic sample points (sigma points). The MAUKF introduces a fading factor to enhance the UKF's adaptability. Implementation considerations include Jacobian matrix calculations for EKF, sigma point propagation for UKF, and adaptive weight adjustments for MAUKF.