Relevant bibliographies by topics / Digital signal processing system

Academic literature on the topic 'Digital signal processing system'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Digital signal processing system"

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Zhuang, Qiu Hui, Guo Jun Liu, Xiu Hua Fu, and San Qiang Wang. "Brain Electrical Signal Digital Processing System Design." Applied Mechanics and Materials 278-280 (January 2013): 958–61. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.958.

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Through the amplification system to extract the brain electrical signal, although already can be displayed, but is not clear; in addition, the analog signal into the computer to carry on the analysis, also must pass to convert analog signals to digital signals (A/D converter).Therefore the need for further use of digital processing, this paper adopts the digital way, on brain electrical analog signal digital filter, through the 40Hz low-pass filter and 50Hz filter, get clear, stable signal, to achieve the design objective.
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Yamaguchi, Hirohisa, and Yoshito Higa. "Digital signal processing acoustic speaker system." Journal of the Acoustical Society of America 116, no. 3 (2004): 1320. http://dx.doi.org/10.1121/1.1809884.

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Hung, Phong, and Vu Duc Vuong. "Analog Signal and Digital Signal Processing in Telecommunication System." Journal La Multiapp 1, no. 6 (January 14, 2021): 1–5. http://dx.doi.org/10.37899/journallamultiapp.v1i6.277.

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The term digital signal is a term from a technology that converts an analog signal into digital data so that the signal can be processed more easily and quickly. The term digital itself is a system that only recognizes two conditions. The two conditions are usually represented by the numbers zero and one, on and off, or others. The smallest unit of digital signal is the bit.
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Zhao, Changhai, Qiuhua Wan, Lihui Liang, and Ying Sun. "Full Digital Processing System of Photoelectric Encoder." Sensors 19, no. 22 (November 9, 2019): 4892. http://dx.doi.org/10.3390/s19224892.

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A photoelectric signal, output by a photoelectric receiver, may detrimentally change after the photoelectric encoder is used for a period of time or when the environment changes; this will directly affect the accuracy of the encoder and lead to fatal errors in the encoder. To maintain its high accuracy, we propose an encoder that can work in a variety of environments and that adopts full digital processing. A signal current that travels from the receiver of a photoelectric encoder is converted into a voltage signal via current limiting resistance. All signals are directly processed in the data processor component of the system. The encoder converts all the signals into its normalized counterpart. Then, the angle of the encoder is calculated using the normalized value. The calculated encoder angle compensates for any error. The final encoder angle is obtained, and the encoder angle is output accordingly. Experiments show that this method can greatly reduce the encoder’s volume. This method also reduces the encoder error from 167 arcseconds to 53 arcseconds. The encoder can still maintain a high accuracy during environmental changes, especially in harsh environments where there are higher accuracy requirements.
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Steffen, Peter. "Digital signal processing." Signal Processing 21, no. 4 (December 1990): 355–56. http://dx.doi.org/10.1016/0165-1684(90)90106-9.

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Ohtsubo, Hiroyasu. "Digital Signal Processing System for Video Camera." Journal of the Institute of Television Engineers of Japan 45, no. 9 (1991): 1060–66. http://dx.doi.org/10.3169/itej1978.45.1060.

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Xu, Ke-Jun, Zhi-Hai Zhu, Yang Zhou, Xiao-Fen Wang, San-Shan Liu, Yun-Zhi Huang, and Zhi-Yuan Chen. "Applied digital signal processing systems for vortex flowmeter with digital signal processing." Review of Scientific Instruments 80, no. 2 (February 2009): 025104. http://dx.doi.org/10.1063/1.3082044.

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Saeed, Amer T., Zaid Raad Saber, Ahmed M. Sana, and Musa A. Hameed. "Eliminating unwanted signals in sound by using digital signal processing system." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 2 (May 1, 2020): 829. http://dx.doi.org/10.11591/ijeecs.v18.i2.pp829-834.

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<p><a name="_Hlk536186602"></a><span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Unwanted signals or noise signals in sound files are considered one of the major challenges and issues for a thousand users. It is impossible to reduce or remove these noise signals without identifying their types and ranges. Therefore, to address one of the big problems in the digital or analogue communication, which is noise signals or unwanted signals, an adaptive selection method and noise signal removal algorithm are proposed in this research. The proposed algorithm is done through specifying the types of undesirable signals, frequency, and time range, then utilizing digital signal processing system which includes design several types of digital filters based on the types and numbers of unwanted signals. Four digital filters are used in this research to remove noise signals from the sound file by implementing the proposed algorithm using Matlab Code. Results show that our proposed algorithm was done successfully and the whole noise signals were removed without any negative consequence in the output sound signal. </span><span style="font-family: 'Times New Roman', serif; font-size: 9pt;">Unwanted signals or noise signals in sound files are considered one of the major challenges and issues for a thousand users. It is impossible to reduce or remove these noise signals without identifying their types and ranges. Therefore, to address one of the big problems in the digital or analogue communication, which is noise signals or unwanted signals, an adaptive selection method and noise signal removal algorithm are proposed in this research. The proposed algorithm is done through specifying the types of undesirable signals, frequency, and time range, then utilizing digital signal processing system which includes design several types of digital filters based on the types and numbers of unwanted signals. Four digital filters are used in this research to remove noise signals from the sound file by implementing the proposed algorithm using Matlab Code. Results show that our proposed algorithm was done successfully and the whole noise signals were removed without any negative consequence in the output sound signal.</span></p>
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Takala, Jarmo, Shuvra S. Bhattacharyya, and Gang Qu. "Embedded Digital Signal Processing Systems." EURASIP Journal on Embedded Systems 2007 (2007): 1. http://dx.doi.org/10.1155/2007/27517.

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Takala, Jarmo, ShuvraS Bhattacharyya, and Gang Qu. "Embedded Digital Signal Processing Systems." EURASIP Journal on Embedded Systems 2007, no. 1 (2007): 027517. http://dx.doi.org/10.1186/1687-3963-2007-027517.

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Dissertations / Theses on the topic "Digital signal processing system"

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Kwan, Ching Chung. "Digital signal processing techniques for on-board processing satellites." Thesis, University of Surrey, 1990. http://epubs.surrey.ac.uk/754893/.

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In on-board processing satellite systems in which FDMA/SCPC access schemes are employed. transmultiplexers are required for the frequency demultiplexing of the SCPC signals. Digital techniques for the implementation of the transmultiplexer for such application were examined in this project. The signal processing in the transmultiplexer operations involved many parameters which could be optimized in order to reduce the hardware complexity whilst satisfying the level of performance required of the system. An approach for the assessment of the relationship between the various parameters and the system performance was devised. which allowed hardware requirement of practical system specifications to be estimated. For systems involving signals of different bandwidths a more flexible implementation of the trans multiplexer is required and two computationally efficient methods. the DFT convolution and analysis/synthesis filter bank. were investigated. These methods gave greater flexibility to the input frequency plan of the transmultiplexer. at the expense of increased computational requirements. Filters were then designed to exploit specific properties of the flexible transmultiplexer methods. resulting in considerable improvement in their efficiencies. Hardware implementation of the flexible transmultiplexer was considered and an efficient multi-processor architecture in combination with parallel processing software algorithms for the signal processing operations were designed. Finally. an experimental model of the payload for a land-mobile satellite system proposal. T -SAT. was constructed using general-purpose digital signal processors and the merits of the on-board processing architecture was demonstrated.
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Li, Shuo. "System-Level Architectural Hardware Synthesis for Digital Signal Processing Sub-Systems." Doctoral thesis, KTH, Elektronik och Inbyggda System, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-180441.

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This thesis presents a novel system-level synthesis framework called System-Level Architectural Synthesis Framework (SYLVA), which synthesizes DigitalSignal Processing (DSP) sub-systems modeled by synchronous data ?ow intohardware implementations in Application-Specific Integrated Circuit (ASIC),Field-Programmable Gate Array (FPGA) or Coarse-Grained ReconfigurableArchitecture (CGRA) style. SYLVA synthesizes in terms of pre-characterizedFunction Implementations (FIMPs). It explores the design space in threedimensions, number of FIMPs, type of FIMPs, and pipeline parallelism be-tween the producing and consuming FIMPs. SYLVA also introduces timingand interface model of FIMPs to enable reuse and automatic generation ofGlobal Interconnect and Control (GLIC) to glue the FIMPs together into aworking system. SYLVA has been evaluated by applying it to several realand synthetic DSP applications and the experimental results are analyzedfor the design space exploration, the GLIC synthesis, the code generation,and the CGRA floorplanning features. The conclusion from the experimentalresults is that by exploring the multi-dimensional design space in terms ofpre-characterized FIMPs, SYLVA explores a richer design space and does itmore effectively compared to the existing High-Level Synthesis (HLS) toolsto improve both engineering and computational efficiency.

QC 20160125

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Nader, Charles. "Enhancing Radio Frequency System Performance by Digital Signal Processing." Licentiate thesis, University of Gävle, Department of Electronics, Mathematics and Natural Sciences, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-7312.

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In this thesis measurement systems for the purpose of characterization of radio frequency power amplifiers are studied. Methods to increase the speed, accuracy, bandwidth, as well as to reduce the sampling requirements and testing cost are presented. A method intended for signal shaping with respect to peak to-average ratio reduction and its effects-improvements on the radio frequency front-end performance is investigated.

A time domain measurement system intended for fast and accurate measurements and characterization of radio frequency power amplifiers is discussed. An automated, fast and accurate technique for power and frequency sweep measurements is presented. Multidimensional representation of measured figure of merits is evaluated for its importance on the production-testing phase of power amplifiers.

A technique to extend the digital bandwidth of a measurement system is discussed. It is based on the Zhu-Frank generalized sampling theorem which decreases the requirements on the sampling rate of the measurement system. Its application for power amplifiers behavioral modeling is discussed and evaluated experimentally.

A general method for designing multitone for the purpose of out-of-band characterization of nonlinear radio frequency modules using harmonic sampling is presented. It has an application with the validation of power amplifiers behavioral models in their out-of-band frequency spectral support when extracted from undersampled data.

A method for unfolding the frequency spectrum of undersampled wideband signals is presented. It is of high relevance to state-of-the-art radio frequency measurement systems which capture repetitive waveform based on a sampling rate that violates the Nyquist constraint. The method is presented in a compact form, it eliminates ambiguities caused by folded frequency spectra standing outside the Nyquist band, and is relevant for calibration matters.

A convex optimization reduction-based method of peaks-to-average ratio of orthogonal frequency division multiplexing signals is presented and experimentally validated for a wireless local area network system. Improvements on the radio frequency power amplifier level are investigated with respect to power added efficiency, output power, in-band and out-of-band errors. The influence of the power distribution in the excitation signal on power amplifier performance was evaluated.

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Al-Breiki, Mohamed Ahmed Mohamed Naser. "Digital signal processing extra-tropical cyclones warning system using WiMAX." Thesis, University of Hertfordshire, 2013. http://hdl.handle.net/2299/10628.

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This research project proposed a unique solution to make use of these base stations to keep all subscribers alerted with warning of possible disaster should that be required. As the current, network does not provide a provision for such a noble approach, a new network model has been developed and simulated to interface a sensor (weather station, WeS), with WiMAX weather station. The weather station is based on DSP processor to receive a digitised sensor values, process these values, analyse them and if they fall within the alert zones, packet them according to WiMAX protocol and send them to subscribers. The developed standard bypasses any commercial network to offer free transmission to subscribers. This setup is also able to extract information on weather condition or react on uncertainty, i.e. disaster scenarios. Natural disasters, such as torrent, tornado/ hurricane, volcano eruption, earthquake, Tsunamis or landslide are increasing. Unfortunately they bring with them human tragedies, environment catastrophes, villages, cities and counties are subject to endless devastation during and after the destructive forces. Water, electricity and gas supply are most disrupted and difficult to restore in short time. However, communication is another item that can be affected adversely but WLAN with specific considerations, should be excluded from the effect. This project presents a solution, albeit minor relative to the maximum effect of the disaster, but will keep the telecommunication/communication in operation. Our novel technique, a “Clone Wireless Wide Area Network (CloneWAN)” is a clone wireless network to the wired Network. In the event of natural calamities, it gives continuity of network operation. It is based on WiMAX. The realization of CloneWAN has been formed and simulated to set the national network of the UAE at its correct form. CloneWAN model has been simulated with Opnet platform. All results revealed that the model is complete. The interface to Alerting System is discussed. Results show that the dynamic behavior of the parameters delay and Throughput of CloneWAN model is stable over various and different load scenarios. WiMAX is a de-facto standard in the current and future network requirement standards. Its main component is the Base Station which is normally stationed in the air, high enough to couple signals from other base stations. It is purpose is merely focused on networking signals for commercial purposes. The suggested hardware interface for the Weather Station is based on DSP SHARC processor. The model has been written in C and simulated under Opnet package. A number of scenarios have been set to represent different disasters worldwide. All results are listed and discussed later in the thesis.
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Sulley, C. E. "A functional multiprocessor system for real-time digital signal processing." Thesis, University of Bath, 1985. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370454.

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This thesis is concerned primarily with the architecture of Digital Signal Computers. The work is supported by the design, development and application of a novel Digital Signal Computer system, the MAC68. The MAC68 is a Functional Multiprocessor, using two independent processors, one of which executes general-purpose tasks, and the other executes sequences of arithmetic. The particular MAC68 design was arrived at after careful evaluation of existing Digital Signal Computer architectures. MAC68 features are fully evaluated via its application to the Sub-Band Coding of speech, and in particular by the development of a 16Kb/s Sub-band Coder using six sub-bands. MAC68 performance was found to be comparable to that of current DSP micros for basic digital filter tasks, and superior for FFT tasks. The MAC68 architecture is a balance of high-speed arithmetic and general- purpose capabilities, and is likely to have a greater range of application than General-Purpose micros or DSP micros used alone. Suggestions are put forward for MAC68 enhancements utilising state-of-the-art hardware and software technologies. Because of the current widespread use of General-Purpose micros, and because of the possible performance gains to be had with the MAC68-type architecture, it is thought that MAC68 architectural concepts will be of value in the design of future high-performance Digital Signal Computer systems.
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Chen, Jen Mei. "Multistage adaptive filtering in a multirate digital signal processing system." Thesis, Massachusetts Institute of Technology, 1993. https://hdl.handle.net/1721.1/127935.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.
Includes bibliographical references (leaves 101-104).
by Jen Mei Chen.
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.
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Lim, Seow-Chuan. "Investigations into the feasibility of digital neuromorphic signal processing circuits." Thesis, Loughborough University, 1999. https://dspace.lboro.ac.uk/2134/28189.

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Modelling of the mammalian auditory system is valuable in understanding perception processes and has benefits in the design of signal processing systems and human prosthetic implants. However, as models increase in complexity, traditional methods of modelling using general purpose computers become very slow. One method of overcoming this is to use electronic implementations of these models. This thesis looks into the feasibility of auditory system implementations in digital technology, through the implementation of the Four-Stage Pitch System for pitch detection in hearing proposed by Hewitt and Meddis.
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Kolb, John. "SIGNAL PROCESSING ABOUT A DISTRIBUTED DATA ACQUISITION SYSTEM." International Foundation for Telemetering, 2002. http://hdl.handle.net/10150/605610.

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International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California
Because modern data acquisition systems use digital backplanes, it is logical for more and more data processing to be done in each Data Acquisition Unit (DAU) or even in each module. The processing related to an analog acquisition module typically takes the form of digital signal conditioning for range adjust, linearization and filtering. Some of the advantages of this are discussed in this paper. The next stage is powerful processing boards within DAUs for data reduction and third-party algorithm development. Once data is being written to and from powerful processing modules an obvious next step is networking and decom-less access to data. This paper discusses some of the issues related to these types of processing.
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Frangakis, G. P. "Digital and microprocessor-based techniques in signal processing and system simulation." Thesis, University of Southampton, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370338.

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Singer, Amy M. (Amy Michelle). "Top-down design of digital signal processing systems." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/40000.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
Includes bibliographical references (leaves 45-46).
by Amy M. Singer.
M.Eng.
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Books on the topic "Digital signal processing system"

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G, Lucas Joseph, and Hodgkiss William S, eds. Digital signal processing: A system design approach. New York: Wiley, 1988.

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Da Silva, Eduardo A. B. (Eduardo Antônio Barros), 1963- and Netto, Sergio L. (Sergio Lima), 1967-, eds. Digital signal processing: System analysis and design. 2nd ed. New York: Cambridge University Press, 2010.

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G, Lucas Joseph, and Hodgkiss William S, eds. Digital signal processing: A system design approach. Chichester: Wiley, 1988.

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1940-, Zhang Yan-Zhong, and Yao Yufen 1940-, eds. Digital signal processing system and its realization. Beijing: Science Press, 1993.

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Nekoogar, Farzad. Digital control using digital signal processing. Upper Saddler River, NJ: Prentice Hall, 1999.

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W, Schafer Ronald, and Yoder M. A, eds. Signal processing first. [Hemel Hempstead]: Pearson Education, 2003.

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Corinthios, Michael. Signals, systems, transforms, and digital signal processing with MATLAB. Boca Raton: Taylor & Francis, 2009.

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1938-, Schafer Ronald W., and Yoder M. A, eds. Signal processing first. Upper Saddle River, NJ: Pearson/Prentice Hall, 2003.

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Kehtarnavaz, Nasser. Digital signal processing system-level design using LabVIEW. Oxford: Elsevier/Newnes, 2005.

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Thomas, Young. Linear systems anddigital signal processing. Englewood Cliffs, NJ: Prentice-Hall, 1985.

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Book chapters on the topic "Digital signal processing system"

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Smirnov, Alexandre. "Imaging System Quality Assessment." In Digital Signal Processing, 171–211. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03855-0_5.

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Mulgrew, Bernard, Peter Grant, and John Thompson. "Signal representation and system response." In Digital Signal Processing, 1–32. London: Macmillan Education UK, 1999. http://dx.doi.org/10.1007/978-1-349-14944-5_1.

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Mulgrew, Bernard, Peter Grant, and John Thompson. "Transfer function and system characterisation." In Digital Signal Processing, 56–84. London: Macmillan Education UK, 1999. http://dx.doi.org/10.1007/978-1-349-14944-5_3.

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Mulgrew, Bernard. "Signal representation and system response." In Digital Signal Processing, 1–32. London: Macmillan Education UK, 2003. http://dx.doi.org/10.1057/978-1-137-44655-8_1.

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Mulgrew, Bernard. "Transfer function and system characterisation." In Digital Signal Processing, 55–84. London: Macmillan Education UK, 2003. http://dx.doi.org/10.1057/978-1-137-44655-8_3.

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Benesty, Jacob, Tomas Gänsler, Dennis R. Morgan, M. Mohan Sondhi, and Steven L. Gay. "Some Practical Aspects of Stereo Teleconferencing System Implementation." In Digital Signal Processing, 133–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04437-7_7.

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Kienle, Frank. "Digital Transmission System." In Architectures for Baseband Signal Processing, 17–36. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8030-3_2.

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Perdikaris, George A. "Digital Signal Processing." In Computer Controlled Systems, 291–321. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-015-7929-2_5.

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Currie, Edward H. "Digital Signal Processing." In Mixed-Signal Embedded Systems Design, 547–98. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70312-7_12.

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Sundararajan, D. "Discrete-Time Systems." In Digital Signal Processing, 37–64. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62368-5_2.

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Conference papers on the topic "Digital signal processing system"

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"W2B: Digital Signal Processing." In 2019 32nd IEEE International System-on-Chip Conference (SOCC). IEEE, 2019. http://dx.doi.org/10.1109/socc46988.2019.9088108.

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Bächer, Dieter. "Audio System Using Digital Signal Processing." In SAE International Congress and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1986. http://dx.doi.org/10.4271/860118.

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Perlot, N., E. Duca, J. Horwath, D. Giggenbach, and E. Leitgeb. "System requirements for optical HAP-satellite links." In Digital Signal Processing (CSNDSP). IEEE, 2008. http://dx.doi.org/10.1109/csndsp.2008.4610724.

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Rinner, D., H. Witschnig, and E. Merlin. "Broadband NFC - A system analysis for the uplink." In Digital Signal Processing (CSNDSP). IEEE, 2008. http://dx.doi.org/10.1109/csndsp.2008.4610713.

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Huang Letian and Li Guangjun. "A reconfigurable system for digital signal processing." In 2008 9th International Conference on Signal Processing (ICSP 2008). IEEE, 2008. http://dx.doi.org/10.1109/icosp.2008.4697165.

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Huang Letian and Li Guangjun. "A reconfigurable system for digital signal processing." In 2008 5th International Multi-Conference on Systems, Signals and Devices (SSD). IEEE, 2008. http://dx.doi.org/10.1109/ssd.2008.4632781.

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"Signal Processing & Digital Image Processing." In 2022 57th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST). IEEE, 2022. http://dx.doi.org/10.1109/icest55168.2022.9828659.

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Kuznetsov, V. S., A. S. Volkov, A. A. Bakhtin, A. V. Solodkov, and V. G. Soroka. "Efficient Digital Modulation Signal System." In 2021 Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO). IEEE, 2021. http://dx.doi.org/10.1109/synchroinfo51390.2021.9488378.

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Olyaee, Saeed, and Shahram Mohammad Nejad. "Reduction of non-orthogonality effect in nanometrology system by modified optics and signal conditioner." In Digital Signal Processing (CSNDSP). IEEE, 2008. http://dx.doi.org/10.1109/csndsp.2008.4610751.

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Toyoshima, M., N. Miyashita, Y. Takayama, H. Kunimori, and S. Kimura. "System analysis of non-mechanical compact optical transceiver for wireless communications with a VCSEL array." In Digital Signal Processing (CSNDSP). IEEE, 2008. http://dx.doi.org/10.1109/csndsp.2008.4610792.

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Reports on the topic "Digital signal processing system"

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Vaidyanathan, P. P. Cyclic LTI Systems in Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, June 1998. http://dx.doi.org/10.21236/ada349622.

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Hebert, Anthony J., and Paul R. Mackin. Advanced Modeling and System Parameter Identification through Minimal Dynamic Stimulation and Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, August 2014. http://dx.doi.org/10.21236/ada609130.

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Thomas, J. B., and K. Steiglitz. Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, December 1988. http://dx.doi.org/10.21236/ada203744.

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Roberts, Richard A. VLSI Implementations for Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, December 1987. http://dx.doi.org/10.21236/ada189612.

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Chung, Y., L. Emery, and J. Kirchman. Digital signal processing for beam position feedback. Office of Scientific and Technical Information (OSTI), April 1992. http://dx.doi.org/10.2172/90669.

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Biglieri, Ezio, and Michele Elia. Applications of Signal Processing in Digital Communications. Fort Belvoir, VA: Defense Technical Information Center, January 1987. http://dx.doi.org/10.21236/ada190420.

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Elia, Michele. Applications of Signal Processing in Digital Communications. Fort Belvoir, VA: Defense Technical Information Center, November 1987. http://dx.doi.org/10.21236/ada190422.

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Willson, Jr, and Alan N. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, December 1993. http://dx.doi.org/10.21236/ada277617.

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Willson, Jr, and Alan N. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, September 1994. http://dx.doi.org/10.21236/ada286483.

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Willson, Alan N., and Jr. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada250365.

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