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Unveiling the Power of System Identification with Quantized Observations: A Comprehensive Guide to Systems Control

Harvey Bell

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Published in System Identification With Quantized Observations (Systems Control: Foundations Applications)

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In the realm of systems engineering, system identification plays a pivotal role in understanding the behavior of dynamic systems and designing effective controllers. With the advent of digitization and the proliferation of sensors, quantized observations have become increasingly prevalent in system identification, leading to the emergence of System Identification with Quantized Observations as a cutting-edge field of research.

Quantized Observations: A Key Element

Quantization refers to the process of converting continuous data into discrete levels, often due to the limitations of sensors or communication channels. In system identification, quantized observations introduce challenges as they can lead to information loss and affect the accuracy of system identification algorithms.

System Identification with Quantized Observations (Systems & Control: Foundations & Applications)

5 out of 5

Language	:	English
File size	:	8247 KB
Print length	:	335 pages

System Identification with Quantized Observations

System Identification with Quantized Observations Systems Control provides a comprehensive framework for understanding the impact of quantization on system identification algorithms and explores techniques for mitigating its effects. This book delves into:

Modeling Quantized Observations: Explores various approaches to model quantized observations, including scalar quantization, vector quantization, and mixed quantization models.

Identification Algorithms for Quantized Observations: Reviews existing algorithms for system identification with quantized observations, covering both traditional and advanced methods such as subspace methods, Kalman filtering, and particle filtering.

Robust and Adaptive Techniques: Investigates robust and adaptive techniques to enhance the performance of system identification algorithms in the presence of quantization noise and other uncertainties.

Experimental Validation: Presents case studies and experimental results to demonstrate the effectiveness of the proposed techniques in practical applications.

Applications and Relevance

System identification with quantized observations has broad applications in various fields, including:

Sensor Networks: Designing reliable algorithms for system identification in wireless sensor networks, where quantization is often necessary to conserve communication bandwidth.

Control Systems: Developing robust controllers for systems with quantized sensors or in scenarios with limited communication capabilities.

Embedded Systems: Identifying the behavior of embedded systems with limited computing resources, where quantization is employed to reduce memory usage and computational complexity.

Value for Professionals

System Identification with Quantized Observations Systems Control is an invaluable resource for researchers, engineers, and practitioners working in the areas of systems engineering, control systems, and signal processing. It offers:

In-depth Knowledge: Provides a comprehensive understanding of the challenges and methods associated with system identification with quantized observations.

Practical Techniques: Presents practical techniques and algorithms for solving real-world system identification problems with quantization.

Cutting-Edge Research: Highlights the latest advancements in this field and provides insights into future research directions.

System Identification with Quantized Observations Systems Control is an essential guide for anyone seeking to harness the power of system identification with quantized observations. This book empowers readers to design effective controllers, enhance the performance of sensor networks, and develop robust embedded systems in a quantized environment.

Free Download your copy today to unlock the full potential of system identification and advance your research or engineering endeavors.

System Identification with Quantized Observations (Systems & Control: Foundations & Applications)

5 out of 5