Academic literature on the topic 'Wireless Processing'

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Journal articles on the topic "Wireless Processing"

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Jiang, Jun, Huan Qu, and Shu Lin Tian. "Study on the Smart Handheld Wireless Oscilloscope." Applied Mechanics and Materials 416-417 (September 2013): 1325–30. http://dx.doi.org/10.4028/www.scientific.net/amm.416-417.1325.

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As the digital acquisition system is featured by increasingly higher technical targets and more complicated applicable conditions, the traditional digital oscilloscope has become incapable of meeting the requirements of real-time processing of sampled data and waveform display on one hand, and unqualified for field test in hard risky conditions on the other. This paper aims for comprehensively enhancing the digital oscilloscopes data processing, image display, human-machine interface and portable adaptability. To that end, it approaches the system composition of improved oscilloscope, and rend
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Bar-Ness, Yeheskel, Petar Popovski, Osvaldo Simeone, and Umberto Spagnolini. "Distributed processing for wireless networks." Journal of Communications and Networks 11, no. 4 (2009): 323–26. http://dx.doi.org/10.1109/jcn.2009.6391345.

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Kandris, Dionisis, and Eleftherios Anastasiadis. "Advanced Wireless Sensor Networks: Applications, Challenges and Research Trends." Electronics 13, no. 12 (2024): 2268. http://dx.doi.org/10.3390/electronics13122268.

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A typical wireless sensor network (WSN) contains wirelessly interconnected devices, called sensor nodes, which have sensing, processing, and communication abilities and are disseminated within an area of interest [...]
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Dağtaş, S., G. Pekhteryev, Z. Şahinoğlu, H. Çam, and N. Challa. "Real-Time and Secure Wireless Health Monitoring." International Journal of Telemedicine and Applications 2008 (2008): 1–10. http://dx.doi.org/10.1155/2008/135808.

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We present a framework for a wireless health monitoring system using wireless networks such as ZigBee. Vital signals are collected and processed using a 3-tiered architecture. The first stage is the mobile device carried on the body that runs a number of wired and wireless probes. This device is also designed to perform some basic processing such as the heart rate and fatal failure detection. At the second stage, further processing is performed by a local server using the raw data transmitted by the mobile device continuously. The raw data is also stored at this server. The processed data as w
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Liu, Li Cheng, Lu Guo Hao, and Rui Hu. "The Design of the Signal Processing Architecture of a Wireless Relay in Heterogeneous Wireless Networks." Advanced Materials Research 403-408 (November 2011): 1728–31. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.1728.

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Focusing on the wireless relay in heterogeneous wireless networks, a new signal processing architecture of a wireless relay has been proposed. And with an example of the heterogeneous wireless network consisted of GSM and CDMA systems, the detailed design is illustrated. The instance of the wireless relay demonstrates the feasibility of the proposed signal processing architecture.
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Singha, Saurabh, and Sulata Mitra. "Query Processing in Hybrid Wireless Network." International Journal of Sensors, Wireless Communications and Control 8, no. 2 (2018): 122–39. http://dx.doi.org/10.2174/2210327908666180611100353.

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Paulraj, A. J., and C. B. Papadias. "Space-time processing for wireless communications." IEEE Signal Processing Magazine 14, no. 6 (1997): 49–83. http://dx.doi.org/10.1109/79.637317.

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Yi, Zhuorui, Tao Gu, and Qing Ma. "Exploration on Signal Processing Performance of Wireless Sensor in Electromagnetic Interference Environment." Wireless Communications and Mobile Computing 2022 (March 7, 2022): 1–12. http://dx.doi.org/10.1155/2022/2970459.

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In order to deeply analyze the performance of Electromagnetic Field (EMF) on wireless sensor Signal Processing (SP), this paper first examines the influencing factors of wireless sensor SP performance based on the relevant theories of EMF and wireless sensor. Then, it discusses the influence of EMF on wireless sensor information Transmission and Reception (T & R) time, Package Reception Rate (PRR), and communication throughput. Furthermore, the Packet Loss Rate (PLR) and Bit Error Rate (BER) of the sensor are described, and finally, a conclusion is drawn. The research findings are as follo
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Arslan tariq and Rafaqat Alam. "A Review on Skin Cancer Data Using Image Processing." Lahore Garrison University Research Journal of Computer Science and Information Technology 2, no. 3 (2018): 29–32. http://dx.doi.org/10.54692/lgurjcsit.2018.020351.

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The wireless industry is going very fast nowadays. We can easily see the evolution from 2G to 3G and now advance to the 4G and 5G network. Before wireless networks, wired networks were commonly used in every field. But there were some disadvantages regarding mobility, quality of service and connectivity. Wired network bounded the region of the working area for the internet and it requires multiple wires to connect computer from one device to another. While on the other hand wireless network is an open source for everyone to use the internet. There is no limitation of the region and no issue re
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Qiu, Zi Xue, Zhi Xin Chen, Jiang Yuan, You Wei Wang, Jie Yang, and Yun Lei Yu. "Design of Sensor-Tag Using Radio Frequency Power to Energize and its Research on Structural Health Monitoring." Applied Mechanics and Materials 330 (June 2013): 373–79. http://dx.doi.org/10.4028/www.scientific.net/amm.330.373.

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A new method of structural health monitoring based on sensor-tags using radio frequency power to energize node wirelessly is proposed. A modular RFID sensor-tag, which has the function of signal conditioning, energy harvesting, and wireless transmission, is designed for some sensing elements commonly used in structural health monitoring, such as resistance strain gauges, piezoelectric ceramic and shape memory alloy (SMA). Sensor-tags receive energy which is the feedback of reader antenna coupling and provide power for sensor nodes. It overcomes defects of wireless sensor network (WSN) powered
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Dissertations / Theses on the topic "Wireless Processing"

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Zhang, Benhong. "Spatial signal processing in wireless sensor networks." [Ames, Iowa : Iowa State University], 2006.

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Ostuni, Francesco Saverio. "Interactive processing for space-time wireless communications." Thesis, King's College London (University of London), 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414014.

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Fang, Zexi. "Sensor array processing : localisation of wireless sources." Thesis, Imperial College London, 2017. http://hdl.handle.net/10044/1/59102.

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In this thesis, various subspace array processing techniques for wireless source localisation are presented and investigated in the following three aspects. First, in the environment of indoor optical wireless communications, the paths of different sources and/or from different reflectors may impinge on the receiver from closely spaced directions with a high probability. In this case, the ranges of the paths, together with their directions, are important especially for isolating the desired source from the interferers. A blind multi-source localisation approach, which can be used as a channel
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Welborn, Matthew Lee 1966. "Flexible signal processing algorithms for wireless communications." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86556.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.<br>Includes bibliographical references (p. 129-132).<br>by Matthew Lee Welborn.<br>Ph.D.
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Tang, Melinda Y. "Wireless reconfigurability of fault-tolerant processing systems." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/53168.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.<br>Includes bibliographical references (p. 55-56).<br>This thesis examines the use of wireless data buses for communication in a real-time computer system designed for applications with high reliability requirements. This work is based on the Draper Laboratory Software Based Redundancy Management System (SBRMS), which is a fault-tolerant system architecture that uses data exchange and voting via Ethernet connections between redundant hardware components to detect and recover fro
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Wang, Yingying. "ADVANCED ANALOG SIGNAL PROCESSING FOR WIRELESS COMMUNICATIONS." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1585776428631869.

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See, Chong Meng Samson. "Space-time processing for wireless mobile communications." Thesis, Loughborough University, 1999. https://dspace.lboro.ac.uk/2134/25284.

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Intersymbol interference (ISI) and co-channel interference (CCI) are two major obstacles to high speed data transmission in wireless cellular communications systems. Unlike thermal noise, their effects cannot be removed by increasing the signal power and are time-varying due to the relative motion between the transmitters and receivers. Space-time processing offers a signal processing framework to optimally integrate the spatial and temporal properties of the signal for maximal signal reception and at the same time, mitigate the ISI and CCI impairments. In this thesis, we focus on the developm
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Hult, Tommy. "Space-time processing applications for wireless communications /." Karlskrona : Department of Signal Processing, Blekinge Institute of Technology, 2008. http://www.bth.se/fou/Forskinfo.nsf/allfirst2/e1b6126417810fe1c12574c90057f665?OpenDocument.

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Xu, Songcen. "Distributed signal processing algorithms for wireless networks." Thesis, University of York, 2015. http://etheses.whiterose.ac.uk/9516/.

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Distributed signal processing algorithms have become a key approach for statistical inference in wireless networks and applications such as wireless sensor networks and smart grids. It is well known that distributed processing techniques deal with the extraction of information from data collected at nodes that are distributed over a geographic area. In this context, for each specific node, a set of neighbor nodes collect their local information and transmit the estimates to a specific node. Then, each specific node combines the collected information together with its local estimate to generate
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Silva, Rone Ilidio da. "Spatial query processing for wireless sensor networks." Universidade Federal de Minas Gerais, 2012. http://hdl.handle.net/1843/ESBF-8SVJT2.

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Wireless sensor networks (WSN) are particularly useful for obtaining data concerning events limited to a well-defined geographic region. Applications for this task typically use spatial queries, which are SQL-like queries where location constraints are imposed on the collected data. Spatial queries save energy since only nodes inside this region collect data. This work provides a general discussion of in-network spatial query processing in WSN. We propose to divide spatial query processing in well-defined stages. This division helps understanding the spatial query processing mechanisms found i
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Books on the topic "Wireless Processing"

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Lu, Jianhua, Xiaoming Tao, and Ning Ge. Structural Processing for Wireless Communications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15711-5.

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Vincent, Poor H., and Wornell Gregory W, eds. Wireless communications: Signal processing perspectives. Prentice Hall PTR, 1998.

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Boccuzzi, Joseph. Signal processing for wireless communications. McGraw-Hill, 2008.

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Boccuzzi, Joseph. Signal processing for wireless communications. McGraw-Hill, 2008.

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Boccuzzi, Joseph. Signal Processing for Wireless Communications. McGraw-Hill, 2008.

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Poor, H. Vincent, and Lang Tong, eds. Signal Processing for Wireless Communication Systems. Springer US, 2002. http://dx.doi.org/10.1007/b101819.

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Hussain, D. M. Akbar, Abdul Qadeer Khan Rajput, Bhawani Shankar Chowdhry, and Quintin Gee, eds. Wireless Networks, Information Processing and Systems. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89853-5.

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Mohamed, Ibnkahla, ed. Adaptive signal processing in wireless communications. Taylor & Francis, 2008.

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Dietrich, Frank A. Robust signal processing for wireless communications. Springer, 2008.

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Vincent, Poor H., and Tong Lang, eds. Signal processing for wireless communication systems. Kluwer Academic, 2002.

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Book chapters on the topic "Wireless Processing"

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Polydoros, Andreas, and Keith M. Chugg. "Per-Survivor Processing (PSP)." In Wireless Communications. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4757-2604-6_3.

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Zhang, Kuan, and Xuemin Shen. "Privacy-Preserving Health Data Processing." In Wireless Networks. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24717-5_5.

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Sheikh, Asrar U. H. "Signal Processing in Wireless Communications." In Wireless Communications. Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-9152-2_7.

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Cao, Jiannong, and Yanni Yang. "Wireless Signals and Signal Processing." In Wireless Networks. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08345-7_2.

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Kilinc, Enver Gurhan, Catherine Dehollain, and Franco Maloberti. "Wireless Communication." In Analog Circuits and Signal Processing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21179-4_4.

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Peng, Mugen, Zhongyuan Zhao, and Yaohua Sun. "Cooperative Signal Processing in Fog Radio Access Networks." In Wireless Networks. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50735-0_4.

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Yılmaz, Gürkan, and Catherine Dehollain. "Wireless Power Transfer." In Analog Circuits and Signal Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49337-4_3.

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Yılmaz, Gürkan, and Catherine Dehollain. "Wireless Data Communication." In Analog Circuits and Signal Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49337-4_4.

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Türe, Kerim, Catherine Dehollain, and Franco Maloberti. "Wireless Data Communication." In Analog Circuits and Signal Processing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40826-8_4.

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Ahmed, Yasir. "The Wireless Channel." In Recipes for Communication and Signal Processing. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2917-7_1.

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Conference papers on the topic "Wireless Processing"

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Nirmala, G., M. P. Haripriya, Mohammed Rizwan Shaik, S. Vijayalakshmi, Jason Elroy Martis, and M. Dinesh Babu. "Signal Processing Techniques for Enhanced Wireless Network Performance." In 2024 2nd International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT). IEEE, 2024. https://doi.org/10.1109/icaiccit64383.2024.10912227.

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Mercadé, Laura, Roberto Llorente, and Alejandro Martinez. "Optomechanical Cavities for All-Optical Microwave Signal Processing." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.th3j.3.

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All-optical microwave signal processing using optomechanical cavities on silicon chips in the optical domain is demonstrated. Demonstrations include low phase noise generation, frequency conversion, and enhanced stability, showing promise for next-generation wireless and satellite communications.
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Ma, Lei, Shreyes N. Melkote, John B. Morehouse, James B. Castle, and James W. Fonda. "On-Line Monitoring of End Milling Forces Using a Thin Film Based Wireless Sensor Module." In ASME 2010 International Manufacturing Science and Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/msec2010-34272.

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A sensor module that integrates a thin film PVDF piezoelectric strain sensor and a wireless data processing/transmitting platform has been designed and implemented for wireless monitoring of the feed force in the slot end milling process. The module, which is mounted on the tool shank, measures the dynamic strain produced in the tool and transmits data wirelessly to the receiver connected to a data acquisition computer. A first principles model based on the Euler-Bernoulli beam theory and constitutive equations of the piezoelectric sensor material is used to transform the wirelessly obtained d
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Poor, H. V. "Signal processing and wireless networks." In ETW '05. The 7th IEEE Emerging Technologies Workshop: Circuits and Systems For 4G Mobile Wireless Communications. IEEE, 2005. http://dx.doi.org/10.1109/emrtw.2005.195668.

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Moore, Linda J., Jason T. Parker, LeRoy A. Gorham, Uttam K. Majumder, Michael J. Minardi, and Steven M. Scarborough. "Staring RF signal processing challenges." In Propagation in Wireless Communications (ICEAA). IEEE, 2011. http://dx.doi.org/10.1109/iceaa.2011.6046357.

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Novo, D., M. Li, B. Bougard, L. Van der Perre, and F. Catthoor. "Finite precision processing in wireless applications." In 2009 Design, Automation & Test in Europe Conference & Exhibition (DATE'09). IEEE, 2009. http://dx.doi.org/10.1109/date.2009.5090851.

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Bor, Martin C., Ioannis Chatzigiannakis, Stefan O. Dulman, Panagiotis Kikiras, Evangelos Theodoridis, and Otto W. Visser. "Post-processing in wireless sensor networks." In the 7th ACM workshop. ACM Press, 2010. http://dx.doi.org/10.1145/1868589.1868597.

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Dostanic, A., A. Peulic, S. Randjic, and U. Pesovic. "Wireless Sensor Network Wavelet Signal Processing." In 2007 14th International Workshop on Systems, Signals and Image Processing and 6th EURASIP Conference focused on Speech and Image Processing, Multimedia Communications and Services. IEEE, 2007. http://dx.doi.org/10.1109/iwssip.2007.4381206.

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Wei, Xuefeng. "Signal Processing System in Wireless Communication." In 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE). IEEE, 2021. http://dx.doi.org/10.1109/icbaie52039.2021.9389961.

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Oztarak, Hakan, Adnan Yazici, Demet Aksoy, and Roy George. "Multimedia Processing in Wireless Sensor Networks." In 2007 Innovations in Information Technologies (IIT). IEEE, 2007. http://dx.doi.org/10.1109/iit.2007.4430410.

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Reports on the topic "Wireless Processing"

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Raghavendra, Cauligi S., and Viktor K. Prasanna. Distributed Signal Processing in Wireless Sensor Networks. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada437824.

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Wornell, Gregory W. Advanced Signal Processing Techniques for Wireless Communications. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada300359.

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Luo, Zhi-Quan. Mathematical Analysis of Signal Processing Capabilities of Wireless Networks. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada499991.

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Wicker, Steven B. Self-Configuring Wireless Transmission and Decentralized Data Processing for Generic Sensor Networks. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada425425.

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Tong, Lang. Wireless Ad-Hoc Networks with Receiver Multipacket Reception: Performance Analysis and Signal Processing. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada430770.

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Krogmeier, J., and Darcy Bullock. Statewide Wireless Communications Project, Volume 2: Inductive Loop Detection of Bicycles and Inductive Loop Signature Processing for Travel Time Estimation. Purdue University, 2008. http://dx.doi.org/10.5703/1288284314219.

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Kong, Zhihao, and Na Lu. Field Implementation of Concrete Strength Sensor to Determine Optimal Traffic Opening Time. Purdue University, 2024. http://dx.doi.org/10.5703/1288284317724.

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In the fast-paced and time-sensitive fields of construction and concrete production, real-time monitoring of concrete strength is crucial. Traditional testing methods, such as hydraulic compression (ASTM C 39) and maturity methods (ASTM C 1074), are often laborious and challenging to implement on-site. Building on prior research (SPR 4210 and SPR 4513), we have advanced the electromechanical impedance (EMI) technique for in-situ concrete strength monitoring, crucial for determining safe traffic opening times. These projects have made significant strides in technology, including the development
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Krogmeier, J., and Darcy Bullock. Statewide Wireless Communications Project,Volume 3 - Data Collection and Signal Processing for Improvement of Road Profiling and Proof of Concept of a Vehicle-Inftrastructure Based Road Surface Monitoring Application. Purdue University, 2008. http://dx.doi.org/10.5703/1288284314220.

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Modlo, Yevhenii O., Serhiy O. Semerikov, Stanislav L. Bondarevskyi, Stanislav T. Tolmachev, Oksana M. Markova, and Pavlo P. Nechypurenko. Methods of using mobile Internet devices in the formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3677.

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An analysis of the experience of professional training bachelors of electromechanics in Ukraine and abroad made it possible to determine that one of the leading trends in its modernization is the synergistic integration of various engineering branches (mechanical, electrical, electronic engineering and automation) in mechatronics for the purpose of design, manufacture, operation and maintenance electromechanical equipment. Teaching mechatronics provides for the meaningful integration of various disciplines of professional and practical training bachelors of electromechanics based on the concep
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