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"Here is a book that provides the classical foundations of invariant imbedding, a concept that provided the first indication of the connection between transport theory and the Riccati Equation. The reprinting of this classic volume was prompted by a revival of interest in the subject area because of its uses for inverse problems. The major part of the book consists of applications of the invariant imbedding method to specific areas that are of interest to engineers, physicists, applied mathematicians, and numerical analysts. A large set of problems can be found at the end of each chapter. Numerous problems on apparently disparate matters such as Riccati equations, continued fractions, functional equations, and Laplace transforms are included. The exercises present the reader with "real-life" situations. The material is accessible to a general audience, however, the authors do not hesitate to state, and even to prove, a rigorous theorem when one is available. To keep the original flavor of the book, very few changes were made to the manuscript; typographical errors were corrected and slight changes in word order were made to reduce ambiguities."

"This unique book addresses advanced linear algebra from a perspective in which invariant subspaces are the central notion and main tool. It contains comprehensive coverage of geometrical, algebraic, topological, and analytic properties of invariant subspaces. The text lays clear mathematical foundations for linear systems theory and contains a thorough treatment of analytic perturbation theory for matrix functions."

"This book presents the first in-depth, complete, and unified theoretical discussion of the two most important classes of algorithms for solving matrix eigenvalue problems: QR-like algorithms for dense problems and Krylov subspace methods for sparse problems. The author discusses the theory of the generic GR algorithm, including special cases (for example, QR, SR, HR), and the development of Krylov subspace methods. Also addressed are a generic Krylov process and the Arnoldi and various Lanczos algorithms, which are obtained as special cases. The chapter on product eigenvalue problems provides further unification, showing that the generalized eigenvalue problem, the singular value decomposition problem, and other product eigenvalue problems can all be viewed as standard eigenvalue problems."

"Reset control systems addresses the analysis for reset control treating both its basic form, and some useful variations of the reset action and reset condition. The issues regarding reset control, concepts and motivation, analysis tools, and the application of design methodologies to real-world examples, are given thorough coverage.The text opens with a historical perspective which moves from the seminal work of the Clegg integrator and Horowitz FORE to more recent approaches based on impulsive/hybrid control systems and explains the motivation for reset compensation. Preliminary material is also included. The focus then turns to stability analysis for systems using techniques which account for various time- and frequency-domain criteria. The final section of the book is centered on control systems design and application. The PI+CI compensator is detailed as are a proposed frequency domain approach using quantitative feedback theory and ideas for design improvement. Design examples are given."

"Ekstraksi fitur merupakan tahap penting dalam pengenalan objek. Fitur yang dihasilkan dalam tahapan ini akan sangat menentukan ke-akuratan suatu objek ketika dikenali. Scale Invariant Feature Transform (SIFT) merupakan suatu metode yang memberikan fitur-fitur khas dan invarian terhadap berbagai jenis perubahan pada citra. Pada skripsi ini akan dibahas tentang SIFT sebagai metode ekstraksi fitur pada pengenalan objek. Selain itu juga akan dilakukan perancangan simulasi untuk menguji kinerja dan performansi SIFT jika digunakan pada pengenalan jenis kendaraan. Performa dari SIFT ini akan diukur dari grafik recall vs. 1-precision yang dihasilkan dan lamanya waktu proses.

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Feature Extraction is an important stage in object recognition. The features generated in this stage will determine the accuracy of object recognition. Scale Invariant Feature Transform (SIFT) is a method which generate a unique features and invariant against various changes in the image. This thesis will discuss about SIFT as a feature extraction method in object recognition. Also a simulation will be design to test the performance of SIFT if used in a vehicle type recognition. The performance of SIFT can be measured from the graph of recall vs. 1-precision and the processing time."