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In this project Self-Organizing Map is proposed to measure image similarity. The facial images associated to the areas of great interest into the network that is neural feed. This scheme offers promising results for face recognition dealing with lighting variation and facial poses and expressions. The Self-Organizing Map has been particularly successful in various pattern recognition tasks involving very noisy signals after supervised fine-tuning of its weight vectors.
This project presents MATLAB-based feature recognition using a back-propagation neural system for automatic speech recognition. The aim is to explore how neural networks can be used to recognize isolated-word messages as an alternative to traditional methodologies. The strategies developed here can be extended to applications such as sonar target recognition and other acoustic signal classification tasks.
This project extracts features that characterize power quality disturbances from recorded voltage and current signals using wavelet and S-transform analysis. Disturbances considered include sag, swell, transients and harmonics. The coefficients are collected and fed to a neural network for classification.
This project investigates the use of artificial neural networks (ANNs) in various kinds of digital circuits and in the field of cryptography. ANNs can perform complex computations and this work explores their application for secure and novel cryptographic schemes.
An intelligent control for photovoltaic systems is developed combining fuzzy logic, neural networks and wavelet analysis. The proposed Hermite Wavelet-embedded Neural Fuzzy (HWNF) gradient estimator is adopted to build a high-performance indirect adaptive MPPT controller. MATLAB results show superior fast response, power quality and efficiency compared to conventional techniques.
This study proposes a fine-tuned fast approximator based on neural networks that uses aggregated traction system information as inputs and outputs. The approximator can be used as an investment planning constraint in optimization, accounting for limits on train traffic intensity relative to system strength.
This paper presents a chaotic neural network (KIII) modeled on olfactory systems and applied to an electronic nose to discriminate volatile organic compounds (VOCs). Feature vectors from a sensor array are input to the network; results show robust generalization and good classification performance compared to conventional back-propagation networks.
Fuzzy control, based on fuzzy logic, provides a means to design controllers closer to human reasoning than traditional crisp systems. Variables are described over a degree range (0–1) rather than true/false, allowing robust control strategies for temperature regulation.
Two real-time energy management strategies are investigated for optimal current split between batteries and ultracapacitors in electric vehicle applications. The first strategy formulates an optimization problem solved using KKT conditions to obtain real-time operation points.
This work presents an image-based approach for human face recognition using 2D-DCT to remove redundant data and extract features. Feature vectors are constructed from DCT coefficients for classification by neural networks.
With advances in power electronics and microprocessors, various PWM techniques for three-phase voltage source inverters are analyzed and implemented in MATLAB/Simulink to compare performance and suitability for industrial applications.
The goal is to detect and locate human faces in color images. Techniques include color analysis, template matching, neural networks, SVMs and model-based detection. The project explores trade-offs across illumination, face variability and backgrounds.
This project studies detection of stressful events using skin conductance (SC) and finger temperature (FT) data. The challenge is pattern variability across individuals; techniques focus on robust feature extraction and classification.
Load balancing addresses overloading risks by transferring loads between areas using switches and control strategies. Fuzzy logic can help determine how much load to transfer to maintain system limits, complementing automatic generation control (AGC).
This research proposes a security system for remote farms combining image processing, MATLAB and AI for surveillance and real-time monitoring. The system supports multiple-object detection and offers recommendations for future image processing and recognition enhancements.
In today\\\'s rapidly advancing era of automation, robotics control systems are
Learn MoreThe financial sector is witnessing a technological revolution with the rise of Large Lang
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In today\\\'s rapidly advancing era of automation, robotics control systems are evolving to meet the demand for smarter, faster, and more reliable performance. Among the many innovations driving this transformation is the use of MCP (Model-based Control Paradigms)
The financial sector is witnessing a technological revolution with the rise of Large Language Models (LLMs). Traditionally used for text analysis, LLMs are now being integrated with powerful platforms like MATLAB to develop financial forecasting models