Feedback Based Orthogonal Digital Filters

Feedback-Based Orthogonal Digital Filters

Feedback-Based Orthogonal Digital Filters: Theory, Applications, and Implementation develops the theory of a feedback-based orthogonal digital filter and examines several applications where the filter topology leads to a simple and efficient solution. The development of the filter structure is linked to concepts in observer theory. Several signal processing problems can be represented as estimation problems, where a parametric representation of the input is used, to try and replicate it locally. This estimation problem can be solved using an identity observer, and the filter topology falls in this framework. Hence the filter topology represents a universal building block that can find application in several problems, such as spectral estimation, time-recursive computation of transforms, etc. Further, because of the orthogonality constraints satisfied by the structure, it also represents a robust solution under finite precision conditions. The book also presents the observer-based viewpoint of several signal processing problems, and shows that problems that are typically treated independently in the literature are in fact linked and can be cast in a single unified framework. In addition to examining the theoretical issues, the book describes practical issues related to a hardware implementation of the building block, in both the digital and analog domain. On the digital side, issues relating to implementation using semi-custom chips (FPGA's), and ASIC design are examined. On the analog side, the design and testing of a fabricated chip, that functions as a multi-sinusoidal phase-locked-loop, are described. Feedback-Based Orthogonal Digital Filters serves as an excellent reference. May be used as a text for advanced courses on the subject.

Feedback-based Orthogonal Digital Filters, Their Application in Signal Processing, and Their VLSI Implementation

Measurement and Data Science

Nowadays, all of us enjoy the worldwide revival of measurement and data science caused by the revolution of sensory devices and the amazing data transmission, storage and processing capabilities available and embedded everywhere. Thanks to the unbelievable amount of recorded information and the theoretical results of measurement and data science, a great deal of newly developed products invade our surroundings and enable previously unconceivable smart services and support. This volume consists of a number of chapters covering the scientific results of researchers working in this field at the Department of Measurement and Information Systems of the Budapest University of Technology and Economics, Hungary. The book reports research results attained by carefully combining some of the classical theories of measurement and data processing. These new approaches and methods contribute to higher quality measurement design and measured data evaluation, and provide hints to find efficient implementations for instrumentation.