MTech Electronics and Communication Engineering projects explore innovations in communication systems, embedded systems, and signal processing. These projects integrate IoT, machine learning, and smart devices, offering students real-world experience while preparing them for careers in research, development, and emerging technologies.
This study uses deep learning, specifically Multi-layer Perceptron models, to automate CS amplifier design, optimizing gain and power efficiency while reducing manual tuning and design iteration time through predictive modeling.
This study presents an optimized 8T SRAM cell using 45nm technology, reducing leakage power while enhancing stability. Simulations show improved noise margins and power efficiency compared to 6T configurations
This study enhances an existing low-noise amplifier (LNA) using Cadence Virtuoso at 90nm, optimizing power consumption while maintaining noise performance. It also implements a differential difference current conveyor transconductance amplifier
This study evaluates Multi-Gate Ferroelectric FETs for high-frequency applications using TCAD Silvaco simulations. The proposed JAM-DG-FE-FET demonstrates superior analog and RF performance compared to conventional, making it a promising candidate for high-frequency systems.
This study compares RNN-CNN and Transformer-based ASR models using LJspeech data. Transformers outperform in scalability and efficiency, while RNN-CNN models excel in local dependencies. Results highlight Transformers' suitability for large-scale speech recognition tasks.