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Andreas Antoniou

Bio: Andreas Antoniou is an academic researcher from University of Victoria. The author has contributed to research in topics: Digital filter & Adaptive filter. The author has an hindex of 38, co-authored 368 publications receiving 6566 citations. Previous affiliations of Andreas Antoniou include Victoria University, Australia & Concordia University Wisconsin.


Papers
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Book
09 Nov 2021
TL;DR: Practical Optimization: Algorithms and Engineering Applications provides a hands-on treatment of the subject of optimization suitable for use in one or two semesters of a first-year graduate course or an advanced undergraduate course.
Abstract: Practical Optimization: Algorithms and Engineering Applications provides a hands-on treatment of the subject of optimization. A comprehensive set of problems and exercises makes the book suitable for use in one or two semesters of a first-year graduate course or an advanced undergraduate course. Each half of the book contains a full semesters worth of complimentary yet stand-alone material. The practical orientation of the topics chosen and a wealth of useful examples also make the book suitable as a reference work for practitioners in the field. Advancements in the efficiency of digital computers and the evolution of reliable software for numerical computation during the past three decades have led to a rapid growth in the theory, methods, and algorithms of numerical optimization. This body of knowledge has motivated widespread applications of optimization methods in many disciplines, e.g., engineering, business, and science, and has subsequently led to problem solutions that were considered intractable not too long ago. Key Features: extensively class-tested provides a complete teaching package with MATLAB exercises and online solutions to end-of-chapter problems includes recent methods of emerging interest such as semidefinite programming and second-order cone programming presents a unified treatment of unconstrained and constrained optimization uses a practical treatment of optimization accessible to broad audience, from college students to scientists and industry professionals provides a thorough appendix with background theory so non-experts can understand how applications are solved from point of view of optimization

584 citations

Book
01 Jan 1979
TL;DR: This text deals with the construction of algorithms that filter data into useful information and starts with the basics and goes on to cover advanced topics such as recursive and non-recursive filters (including optimization techniques), wave digital filters and DFTs.
Abstract: This text deals with the construction of algorithms that filter data into useful information. It starts with the basics and goes on to cover advanced topics such as recursive and non-recursive filters (including optimization techniques), wave digital filters and DFTs. A new chapter on the application of digital signal processing offers up-to-date techniques and there are new problems and examples throughout. Other features new to this second edition include chapters on quasi-Newton and minimax optimization algorithms for the design of recursive filters and equalizers, and efficient and robust algorithms for the design of non-recursive filters and differentiators. HLP computer language is now replaced with Pascal.

486 citations

Book
01 Jan 1992
TL;DR: Presents basic theories, techniques, and procedures used to analyze, design, and implement two-dimensional filters; and surveys a number of applications in image and seismic data processing that demonstrate their use in real-world signal processing.
Abstract: Presents basic theories, techniques, and procedures used to analyze, design, and implement two-dimensional filters; and surveys a number of applications in image and seismic data processing that demonstrate their use in real-world signal processing. For graduate students in electrical and computer e

475 citations

Book
01 Mar 1984

291 citations

Book
10 Oct 2005
TL;DR: This chapter discusses the Fourier Series and Fourier Transfer, and the design of Recursive Filters Using Optimization Methods and Effects of Finite Word Length in Digital Filters.
Abstract: PREFACE Chapter 1: Introduction to Digital Signal Processing Chapter 2: The Fourier Series and Fourier Transfer Chapter 3: The z Transform Chapter 4: Discrete-Time Systems Chapter 5: Application of the z Transform Chapter 6: The Sampling Process Chapter 7: The Discrete Fourier Transform Chapter 8: Realization of Digital Filters Chapter 9: Design of Nonrecursive (FIR) Filters Chapter 10: Approximations for Analog Filters Chapter 11: Design of Recursive (IIR) Filters Chapter 12: Recursive (IIR) Filters Satisfying Prescribed Specifications Chapter 13: Random Signals Chapter 14: Effects of Finite Word Length in Digital Filters Chapter 15: Design of Nonrecursive Filters Using Optimization Methods Chapter 16: Design of Recursive Filters Using Optimization Methods Chapter 17: Wave Digital Filters Chapter 18: Digital Signal Processing Applications APPENDIX A: COMPLEX ANALYSIS APPENDIX B: ELLIPTIC FUNCTIONS INDEX

277 citations


Cited by
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Journal Article
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

13,333 citations

Journal Article
TL;DR: The continuing convergence of the digital marketing and sales funnels has created a strategic continuum from digital lead generation to digital sales, which identifies the current composition of this digital continuum while providing opportunities to evaluate sales and marketing digital strategies.
Abstract: MKT 6009 Marketing Internship (0 semester credit hours) Student gains experience and improves skills through appropriate developmental work assignments in a real business environment. Student must identify and submit specific business learning objectives at the beginning of the semester. The student must demonstrate exposure to the managerial perspective via involvement or observation. At semester end, student prepares an oral or poster presentation, or a written paper reflecting on the work experience. Student performance is evaluated by the work supervisor. Pass/Fail only. Prerequisites: (MAS 6102 or MBA major) and department consent required. (0-0) S MKT 6244 Digital Marketing Strategy (2 semester credit hours) Executive Education Course. The course explores three distinct areas within marketing and sales namely, digital marketing, traditional sales prospecting, and executive sales organization and strategy. The continuing convergence of the digital marketing and sales funnels has created a strategic continuum from digital lead generation to digital sales. The course identifies the current composition of this digital continuum while providing opportunities to evaluate sales and marketing digital strategies. Prerequisites: MKT 6301 and instructor consent required. (2-0) Y MKT 6301 (SYSM 6318) Marketing Management (3 semester credit hours) Overview of marketing management methods, principles and concepts including product, pricing, promotion and distribution decisions as well as segmentation, targeting and positioning. (3-0) S MKT 6309 Marketing Data Analysis and Research (3 semester credit hours) Methods employed in market research and data analysis to understand consumer behavior, customer journeys, and markets so as to enable better decision-making. Topics include understanding different sources of data, survey design, experiments, and sampling plans. The course will cover the techniques used for market sizing estimation and forecasting. In addition, the course will cover the foundational concepts and techniques used in data visualization and \"story-telling\" for clients and management. Corequisites: MKT 6301 and OPRE 6301. (3-0) Y MKT 6310 Consumer Behavior (3 semester credit hours) An exposition of the theoretical perspectives of consumer behavior along with practical marketing implication. Study of psychological, sociological and behavioral findings and frameworks with reference to consumer decision-making. Topics will include the consumer decision-making model, individual determinants of consumer behavior and environmental influences on consumer behavior and their impact on marketing. Prerequisite: MKT 6301. (3-0) Y MKT 6321 Interactive and Digital Marketing (3 semester credit hours) Introduction to the theory and practice of interactive and digital marketing. Topics covered include: online-market research, consumer behavior, conversion metrics, and segmentation considerations; ecommerce, search and display advertising, audiences, search engine marketing, email, mobile, video, social networks, and the Internet of Things. (3-0) T MKT 6322 Internet Business Models (3 semester credit hours) Topics to be covered are: consumer behavior on the Internet, advertising on the Internet, competitive strategies, market research using the Internet, brand management, managing distribution and supply chains, pricing strategies, electronic payment systems, and developing virtual organizations. Further, students learn auction theory, web content design, and clickstream analysis. Prerequisite: MKT 6301. (3-0) Y MKT 6323 Database Marketing (3 semester credit hours) Techniques to analyze, interpret, and utilize marketing databases of customers to identify a firm's best customers, understanding their needs, and targeting communications and promotions to retain such customers. Topics

5,537 citations