Sensor Signal Processing for Intelligent Systems
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Beschreibung
This edited book provides a comprehensive exploration of the latest advancements and methodologies in signal processing for intelligent systems. The book serves as a multidisciplinary reference, integrating theoretical foundations, algorithmic developments, and real-world applications across diverse domains, including healthcare, agriculture, environmental monitoring, and human activity recognition. By consolidating recent advancements and cross-domain insights, this book bridges the gap between theory and practice in sensor signal processing for intelligent systems. It fosters interdisciplinary collaboration and stimulates further research in the development of more efficient and scalable intelligent systems for diverse applications.
This edited book provides a comprehensive exploration of the latest advancements and methodologies in signal processing for intelligent systems. The book serves as a multidisciplinary reference, integrating theoretical foundations, algorithmic developments, and real-world applications across diverse domains, including healthcare, agriculture, environmental monitoring, and human activity recognition. By consolidating recent advancements and cross-domain insights, this book bridges the gap between theory and practice in sensor signal processing for intelligent systems. It fosters interdisciplinary collaboration and stimulates further research in the development of more efficient and scalable intelligent systems for diverse applications.
Provides an in-depth exploration of sensing and signal processing techniques Combines insights from CS, electrical and biomedical engineering, environmental science, and agricultural technology Presents case studies and practical implementations of intelligent systems in real-world scenarios
Autor*in
Khalid Raza
Themen in »Sensor Signal Processing for Intelligent Systems«
Sensing Systems Signal Processing Intelligent Systems Healthcare Applications Precision Agriculture Environmental Monitoring Human Activity Recognition Machine Learning Data Analysis Predictive Modeling