MATLAB Implementation of D-S Evidence Theory with Conflict Compensation
D-S Evidence Theory: An improved method based on set intersection and union operations that compensates for evidence conflicts through evidence combination rules.
Batch-OMP: An Enhanced Orthogonal Matching Pursuit Algorithm with Batch Processing
Batch-OMP is an improved variant of the Orthogonal Matching Pursuit (OMP) algorithm that achieves faster computational speeds through batch processing while minimizing memory usage compared to conventional OMP implementations.
Wavelet-Bilinear Super-Resolution Reconstruction with Local Adaptive Interpolation
The conventional wavelet-bilinear super-resolution reconstruction method often suffers from mismatched low-frequency and high-frequency coefficients, leading to grayscale deviations in the resulting high-resolution image. This paper introduces an improved approach by incorporating local adaptive interpolation, resulting in a more robust reconstruction algorithm—specifically, a wavelet-local adaptive interpolation hybrid method. The enhanced algorithm aligns coefficient distributions through pixel-adaptive weighting and interpolation kernels, reducing reconstruction artifacts.
Denoising Methods Using Compressive Sensing Reconstruction Algorithms
Denoising techniques based on compressive sensing reconstruction algorithms, including a range of improved methodologies and implementation approaches
Enhanced Frame Difference Method Algorithm
This personally improved and debugged inter-frame difference method serves as a valuable resource for developers studying vehicle detection algorithms, with optimized code implementation and parameter tuning.
Enhanced Data Association Process in SLAM Algorithm
This paper presents a practical improvement for the data association process in SLAM algorithms by combining Euclidean distance with Mahalanobis distance. The algorithm efficiently narrows down the search scope for feature matching by first applying simpler Euclidean distance calculations before computing more complex Mahalanobis distances. Simulation results using synthetic data demonstrate that our enhanced method significantly reduces computational load and improves association efficiency without increasing incorrect associations.
Shaping Filter Method, Jakes Simulation Model and Its Multiple Improved Methods
This work begins with analyzing the statistical characteristics of Rayleigh fading channels and presents the Clarke model based on this foundation. It then proposes simulation methods including the shaping filter approach, Jakes simulation model, and various improved versions. The software implementation process of these simulation models is elaborated, with computer simulations performed using MATLAB. The simulation results demonstrate high matching accuracy between the proposed models and theoretical curves, effectively simulating wireless fading channels through detailed signal analysis.
Enhanced Adaptive Segmentation Method
My improved adaptive segmentation approach incorporates the threshold obtained from Otsu's method as the initial threshold, effectively enhancing both processing speed and segmentation performance
FLICM: A Fuzzy Local Information C-Means Clustering Algorithm with Enhanced Robustness
FLICM represents a recent advancement in fuzzy clustering, building upon traditional FCM methods with superior robustness and performance. This algorithm integrates local spatial information with fuzzy clustering principles, featuring improved noise immunity and clustering accuracy through a novel fuzzy local similarity measure implemented in its objective function.
Numerical Computation of Lyapunov Exponents
Numerical calculation of Lyapunov exponents through phase space reconstruction using row-wise methods and improved computational approaches for enhanced accuracy