Digital Signal Processing: Theory, Practice and Applications
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Digital Signal Processing (DSP) involves the manipulation of signals in digital form to improve, interpret, or transform them. Signals, which can be audio, video, or sensor data, are converted from analog to digital using an Analog-to-Digital Converter (ADC). DSP algorithms then process these digitized signals to perform functions such as filtering, compression, error detection, and enhancement. Key applications of DSP include telecommunications, audio and speech processing, radar and sonar, medical imaging, and multimedia. By leveraging mathematical techniques, DSP enhances signal clarity, re...
Digital Signal Processing (DSP) involves the manipulation of signals in digital form to improve, interpret, or transform them. Signals, which can be audio, video, or sensor data, are converted from analog to digital using an Analog-to-Digital Converter (ADC). DSP algorithms then process these digitized signals to perform functions such as filtering, compression, error detection, and enhancement. Key applications of DSP include telecommunications, audio and speech processing, radar and sonar, medical imaging, and multimedia. By leveraging mathematical techniques, DSP enhances signal clarity, reduces noise, and ensures efficient data transmission and storage. The processed digital signals can then be converted back to analog form through a Digital-to-Analog Converter (DAC) for practical use. This book is a compilation of chapters that discuss the most vital concepts and emerging trends in the field of Digital Signal Processing. Such selected concepts that redefine signal manipulation have been presented in this book. Scientists and students actively engaged in this field will find this book full of crucial and unexplored concepts.
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