Kartik Saini

ORCID: 0000-0002-6016-4993
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Neural Networks and Applications
  • Fault Detection and Control Systems
  • Advanced Algorithms and Applications
  • Adaptive Control of Nonlinear Systems
  • Advanced Control Systems Optimization
  • Control Systems and Identification
  • Handwritten Text Recognition Techniques
  • Text and Document Classification Technologies
  • Adaptive Dynamic Programming Control
  • Advanced Sensor and Control Systems
  • Vehicle License Plate Recognition

Delhi Technological University
2023-2024

National Institute of Technology Kurukshetra
2023

Netaji Subhas University of Technology
2023

ABES Engineering College
2023

Handwritten text recognition is a difficult task with numerous applications in document analysis, postal automation, and historical preservation. There has been substantial progress handwritten methods recent years, ranging from traditional machine learning-based approaches to deep methods. This survey paper provides an in-depth look at the current for recognizing text, emphasis on most promising techniques. The discusses variety of topics, such as data pre-processing, feature extraction,...

10.1109/icseiet58677.2023.10303304 article EN 2023-09-14

Summary This research article presents an artificial neural network (ANN)‐based indirect adaptive control method for nonlinear dynamical systems. In this article, a modified Elman recurrent (MERNN) is proposed as identifier and controller controlling The architecture of the form existing network. parameter training ANN‐based controllers obtained by using most popular optimization algorithm which known back‐propagation algorithm. A comparative study includes Elman, Diagonal, Jordan,...

10.1002/acs.3823 article EN International Journal of Adaptive Control and Signal Processing 2024-05-03

Abstract In this paper, a novel Modified Jordan Recurrent Neural Network (MJRNN) model is presented to identify complex nonlinear dynamical systems. The dynamic system identification using artificial neural networks the most commonly used method in control engineering, due their capabilities. structure of an extended version original recurrent network model. parameter update equations are obtained by back-propagation optimization algorithm, which frequently as learning approach for training...

10.21203/rs.3.rs-2894875/v1 preprint EN cc-by Research Square (Research Square) 2023-07-10
Coming Soon ...