IEEE

Global Asymptotic Stabilization Control for Uncertain Nonlinear Systems With Input Quantization and Unknown Output Function

Abstract: In this article, a global output feedback control scheme is developed for a class of uncertain nonlinear systems subject to input quantization and unknown output function. By employing a ...
Scientific Research Publishing

Saha, A. (2023). An Empirical Comparison of Linear and Non-linear Classification Using Support Vector Machines. International Journal of Computer Sciences and Engineering, 11 ...

ABSTRACT: Support vector machines are recognized as a powerful tool for supervised analysis and classification in different fields, particularly geophysics. In summary, SVMs are binary classifiers.
Scientific Research Publishing

Kim, H.-C., Pang, S., Je, H. M., Kim, D., & Bang, S. Y. (2003). Constructing Support Vector Machine Ensemble. Pattern Recognition, 36, 2757-2767.

ABSTRACT: Support vector machines are recognized as a powerful tool for supervised analysis and classification in different fields, particularly geophysics. In summary, SVMs are binary classifiers.
IEEE

Modeling of IC Buffers from Channel Responses via Machine Learning Kernel Regression

Abstract: This paper investigates the potential of a fully behavioral approach for the generation of accurate models of digital IC buffers based on conventional kernel regressions. The proposed ...