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Digital signal

About: Digital signal is a research topic. Over the lifetime, 44213 publications have been published within this topic receiving 345279 citations.


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Patent
11 Jul 1994
TL;DR: In this article, a digital signal processor for processing various types of signals, such as an image signal and an audio signal, a basic signal processing part, a programmable logic part, and a bus for connecting these parts together.
Abstract: A digital signal processor for processing various types of signals, such as an image signal and an audio signal, a basic signal processing part, a programmable logic part, and a bus for connecting these parts together. Circuit configuration data is transferred to the programmable logic part from an external memory through a data input/output line and the bus under control of the basic signal processing part. The circuit configuration data corresponds to the types of signal processing that is to be performed, and several different types of signal processings can be performed successively.

178 citations

Journal ArticleDOI
TL;DR: A new biochip consisting of an array of microelectrodes with fully-integrated analog and digital circuitry realized in an industrial CMOS process addresses signal degradation and array size issues, thereby facilitating simultaneous stimulation and recording of electrogenic cell activity.

177 citations

Journal ArticleDOI
TL;DR: This paper presents a meta-modelling architecture suitable for high-performance digital signal processing (DSP) for microwave and millimeter-wave radio systems with real-time requirements.
Abstract: Today's exploding demand for faster, more reliable, and ubiquitous radio systems in communication, instrumentation, radar, and sensors poses unprecedented challenges in microwave and millimeter-wave engineering. Recently, the predominant trend has been to place an increasing emphasis on digital signal processing (DSP). However, while offering device compactness and processing flexibility, DSP suffers fundamental drawbacks, such as high-cost analog-digital conversion, high power consumption, and poor performance at high frequencies.

176 citations

Patent
Hirohide Miwa1, Eiichi Shiratori1
09 Jan 1978
TL;DR: In this paper, the authors proposed a broadcast acknowledgement method and system where a digital information signal, generated in order to indicate the content with regard to a present broadcast program (for example, a commercial broadcast program on television, radio or CATV), is superimposed on the voice signal of said program for broadcast and the composite signal transmitted to the receiving station, where it is processed to retrieve the digital information signals.
Abstract: A broadcast acknowledgement method and system wherein a digital information signal, generated in order to indicate the content with regard to a present broadcast program (for example, a commercial broadcast program on television, radio or CATV), is superimposed on the voice signal of said program for broadcast and the composite signal transmitted to the receiving station, where it is processed to retrieve the digital information signal. Thereby, it can be confirmed whether or not the particular program has been broadcast or not. The method generally comprises the steps of removing the particular frequency band of the voice signal, generating the digital information signal by using some of the desired frequency signals within the particular frequency band of the voice signal, superimposing the digital information signal on the voice signal, transmitting the composite signal, extracting the digital information signal from the received signal at the receiving side, and processing the digital information signal so extracted to identify the particular program broadcast, and thus to obtain broadcast acknowledgement information such as sponsor's name, performers' name, time of broadcasting, etc. The broadcast acknowledgement system comprises, in several embodiments, a voice amplifier, band elimination filters, digital information generation circuit, various signal generators, and a mixing circuit; and, in another embodiment, a voice amplifier, band elimination filters, a digital information generation circuit, and a selector circuit.

176 citations

Journal ArticleDOI
TL;DR: This new textbook by R. E. Blahut contains perhaps the most comprehensive coverage of fast algorithms todate, with an emphasis on implementing the two canonical signal processing operations of convolution and discrete Fourier transformation.
Abstract: This new textbook by R. E. Blahut, which deals with the theory and design of efficient algorithms for digital signal processing, contains perhaps the most comprehensive coverage of fast algorithms todate.Alargecollectionofalgorithmsistreated,withanemphasis on implementing the two canonical signal processing operations of convolution and discrete Fourier transformation. In recent years, there has been much work done on fast algorithms,andBlahutdoesafinejobofblendingmaterialfromdiverse sources to form a coherent and self-contained approach to his subject.The mathematical level of this book is high, reflecting the rather abstract nature of the theoretical underpinnings of fast computational techniques. Although electrical engineers are forthe most part mathematically sophisticated, they tend to lack training in abstract algebra and number theory, both of which are essential to any thorough discussion of fast algorithms. Thus this audience should find the tutorial chapters which the text provides on these topics to be quite helpful. An additional feature of the text, which the nonspecialist should find useful, is that each new algorithm is described through three different formats: a simple example, a flowchart, and a set of matrix equations. This use of repetition assists the reader in grasping subject matter which for the most part is nonintuitive. Operation counts (as measured by the number of multiplications and the number of additions) for each algorithm are tabulated for avarietyof blocklengths (i.e., lengths of data segments), making performance comparisons easy. As the author points out, run-time comparisons may be quite different. Each chapter concludes with a set of problems of varying difficulty. These problems are well integrated with the text and serve to supplement the many examples worked out in the text. The book is devoted to how one rapidly computes various mathematical operators such as transform and convolutions. For a deeper understanding of the meaning of theseoperators,one must consult other sources in which their use is discussed. The text emphasizes algorithms which employ a reduced, or minimum, numberof muItiplications,althoughadditioncountsarealsotaken into consideration. However, an algorithm which is the “fastest” as measured in arithmetic operation counts may not be the fastest in execution time, particularly if dedicated hardware is employed. Indeed in practiceother considerationsfrequentlypropel oneaway from the computationally ”optimal” algorithm. Much work has been done on the theory and application of signal processing algorithms which are “efficient” in terms other than rnultiply/add counts, such as roundoff noise, limit cycles, coefficient quantization, memory access, hardware costs, etc. It is clearly necessary to limit the scope of any treatise, and the exclusion of differing performance measures is certainly appropriate. A description of the contents of the book will now be given, followed by some concluding remarks of a more general nature. Chapter 2 i s a tutorial on abstract algebra. It i s quite readable and is liberally laced with examples. In addition to the standard modern algebra fare (groups, rings, fields, vector spaces, matrices), the ubiquitous Chinese remainder theorem is discussed in detail. Chapters 3 and 4, and their extensions in Chapters 7and 8, form the core of the text. The third chapter addresses fast algorithms for short convolutions. The Cook-Toom convolution algorithm is discussed, followed by the Winograd convolution algorithm. A proof of the optimality of the Winograd algorithm, with respect to multiplications, for performing cyclic convolutions, is presented at the close of the chapter. The fourth chapter addresses fast algorithms for computing the discrete Fourier transform. The CooleyTukey algorithm is considered first. The approach taken is to view this algorithm as a means of mapping a onedimensional Fourier transform into a multidimensional transform. Variations of the algorithm are discussed, including the Rader-Brenner transform. Next, the Good-Thomas algorithm is discussed. This algorithm is again presented as a means of mapping a onedimensional transform into a higher dimensional transform, this time based on the Chinese remainder theorem. Rader’s algorithm for computing primelength Fouriertransforms by useofconvolution ispresented next. Extensions of the algorithm to blocklengths which are the power of an odd prime are considered. The chapter closes with the Winograd-Fourier transform which builds upon the Rader prime algorithm. Certain short blocklengthsareconsidered in detail,and the corresponding algorithms are compiled into an Appendix. Chapter 5 i s a mathematical interlude, tutorially covering items from number theory and algebraic field theory which are needed in later chapters. Topics include the totient function, Euler’s theorem, Fermat’s theorem, minimal polynomials, and cyclotomic polynomials. Chapter 6 is devoted to number theoretic transforms. These transforms proceed by representing the data values themselves in the field of integers modulo a prime. Convolution in integer fields is also covered. Chapters 7and 8 extend the convolution and transform methods of Chapters 3 and 4 to higher dimensions. Multidimensional transforms (convolutions) are used both to efficiently compute onedimensional transforms (convolutions) and to process data which are inherently higher dimensional. Both applications are treated in these chapters. Topics include the Agarwal-Cooley convolution algorithm, polynomial transforms, the family of Johnson-Burrus transforms and the Nussbaumer-Quandalle FFT. Chapter 9 discusses architectures for transforms and digital filters and includes treatmentsof FFT butterfly networks and overlapadd convolution. The remaining three chapters are mostly independent from the rest of the book. Chapter 10 covers fast algorithms based on doubling strategies. Computational tasks for which such fast algorithms are derived include sorting, matrix transposition, matrix multiplication, polynomial division, computation of trigonometric functions, and coordinate rotation. Many of theseoperations arise as steps in the solution of oneor more signal processing problems. Fast algorithms for solving Toeplitz systems is the theme of Chapter 11. There is a variety of fast algorithms discussed, the proper choice of which depends on the specific structure of the Toeplitz system at hand (such as whether or not the system is symmetric and whether or not the right-hand vector is arbitrary). The final chapter addresses fast algorithms for Trellis and tree search and includes the Viterbi, Stack, and Fano algorithms. These

175 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20239
202225
2021190
2020755
2019942
2018915