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A signal represents data as waves or pulses, often in continuous form. It focuses on data extraction and transmission in Electrical and Electronics Engineering.
Deep Learning is a subset of Machine Learning inspired by the human brain's structure. It uses algorithms to analyze data and derive insights, mimicking human decision-making.
Power engineering focuses on the generation, transmission, and distribution of electric power, along with devices like generators, motors, and transformers essential to these systems.
A control system is a set of commands or rules that regulate a system's functionality to achieve desired outputs efficiently.
Machine learning enables computers to learn and improve from data without explicit programming. It is a key aspect of Artificial Intelligence, focusing on creating applications that analyze data and adapt autonomously.
Digital filters are vital in signal processing, removing noise, enhancing quality, and preparing signals for further analysis. They are used for tasks like noise reduction, signal smoothing, and recovery.
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Image Processing provides a comprehensive set of reference-standard algorithms and workflow apps for image processing, analysis, visualization, and algorithm development.
A neural network is an adaptive system that learns by using interconnected nodes or neurons in a layered structure that resembles a human brain. A neural network can learn from data so it can be trained to recognize patterns, classify data, and forecast future events.
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