Vehicle Counting in Video Streams
MATLAB-based vehicle counting from video streams with direct usability - accepts .avi files as input
Signal-to-Noise Ratio Before and After Image Transformation
This program computes and returns the signal-to-noise ratio (SNR) before and after image transformation, requiring only the input of an image filename to generate results
Gray Model Prediction with MATLAB
This MATLAB implementation of Gray Model prediction allows users to specify the number of forecast years through a simple graphical interface input. The program utilizes GM(1,1) modeling methodology for time series forecasting.
Determining Image Binarization Threshold via Maximum Entropy Method with Input Image Name
Implementation of maximum entropy method for calculating image binarization threshold using input image name, reading image file M to statistically analyze probability distribution of gray levels
Drawing Circles on Images
Drawing circles on images, supports binary or grayscale image inputs. This function is commonly implemented using coordinate calculation algorithms and can be integrated into image processing pipelines.
Convolutional Coding: A Memory-Based Encoding Technique with Code Implementation Insights
Convolutional code is a memory-based encoding technique where at any given time unit, the encoder's n outputs depend not only on the current k inputs but also on the previous m inputs. Typically denoted as (n, k, m), this simulation employs a (2, 1, 3) convolutional code structure. The implementation involves shift registers for memory management and polynomial generators for output computation.
Electric Vehicle Tire Slip Angle Simulink Simulation Model
Electric Vehicle Tire Slip Angle Simulink Simulation Model with inputs including front wheel steering angle, vehicle yaw rate, longitudinal velocity, and lateral velocity. The model implements dynamic calculations to simulate tire behavior under various driving conditions.
Autoregressive Load Forecasting Using Genetic Algorithm
This implementation utilizes genetic algorithms to predict next-day load by processing seven consecutive days of historical load data as input features, suitable for power systems and transportation optimization.
MATLAB Implementation of Cubic Spline Interpolation with Algorithm Explanation
This MATLAB .m program implements cubic spline interpolation using a 2D input array A(Nx2). The interpolation method follows the formula: S(x) = A(J) + B(J)*(x - x(J)) + C(J)*(x - x(J))**2 + D(J)*(x - x(J))**3 for x(J) <= x < x(J+1), with detailed coefficient calculation and boundary handling.
Design of a Source Space
Designing a Source Space 1.1 Use input function to obtain the number of probability components in the source space 1.2 Verify the completeness of the probability space 1.3 Calculate the information entropy of the probability space