SVM Toolbox with Comprehensive Waveform and Image Processing Capabilities

This premier Support Vector Machine (SVM) toolbox represents the most advanced solution available, featuring comprehensive capabilities for waveform and image processing. The toolbox incorporates powerful algorithms including kernel methods (linear, polynomial, RBF) and optimization techniques, along with extensive feature extraction and data processing methods. With this toolbox, users can efficiently perform waveform and image preprocessing using functions like signal filtering and image normalization, feature extraction through techniques such as wavelet transforms and histogram of oriented gradients, classification tasks employing multi-class SVM implementations, and regression analysis. The toolbox provides an intuitive interface with key functions like svm_train() for model training and svm_predict() for classification, making it accessible for both beginners and professionals. It finds applications across diverse domains including signal processing, image recognition, and pattern recognition, enabling users to effectively process and analyze waveform and image data through well-documented code examples and modular architecture.