Bibliografie tematiche / CONTROL SIGNAL

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  2. Tesi
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Letteratura scientifica selezionata sul tema "CONTROL SIGNAL"

Autore: Grafiati
Pubblicato: 11 settembre 2023
Ultima modifica: 26 luglio 2025

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Articoli di riviste sul tema "CONTROL SIGNAL"

1

Shellenberger, Richard O., and Paul Lewis. "Signal Control by Six Signals." Psychological Reports 63, no. 1 (1988): 311–18. http://dx.doi.org/10.2466/pr0.1988.63.1.311.

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In previous signal-control experiments, several types of stimuli elicited pecking when paired with peck-contingent grain. Here, we compared the effectiveness of an auditory stimulus and five visual stimuli. For 12 pigeons, the first keypeck to follow the offset of a 4-sec. signal was reinforced with grain. We examined the following signals: a tone, a white keylight, a dark keylight, a keylight that changed from white to red, houselight onset, and houselight offset. All signals acquired strong control over responding. According to one measure, percent of signals with a peck, houselight offset s
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K Avzekar Amruta, Minal. "Adaptive Traffic Signal Control with VANET." International Journal of Scientific Engineering and Research 2, no. 3 (2014): 30–32. https://doi.org/10.70729/1140306.

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Logan, Gordon D., Russell J. Schachar, and Rosemary Tannock. "Impulsivity and Inhibitory Control." Psychological Science 8, no. 1 (1997): 60–64. http://dx.doi.org/10.1111/j.1467-9280.1997.tb00545.x.

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We report an experiment testing the hypothesis that impulsive behavior reflects a deficit in the ability to inhibit prepotent responses Specifically, we examined whether impulsive people respond more slowly to signals to inhibit (stop signals) than non-impulsive people In this experiment, 136 undergraduate students completed an impulsivity questionnaire and then participated in a stop-signal experiment, in which they performed a choice reaction time (go) task and were asked to inhibit their responses to the go task when they heard a stop signal The delay between the go signal and the stop sign
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4

Meghani, Jayesh, Gaurav Gumbade, and Komal A. Chaudhari. "Intelligent RF-ID based Traffic Signal Control." International Journal of Science and Research (IJSR) 12, no. 11 (2023): 1858–61. http://dx.doi.org/10.21275/mr231125163753.

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Lacefield, Soni, and Nicholas Ingolia. "Signal Transduction: External Signals Influence Spore-Number Control." Current Biology 16, no. 4 (2006): R125—R127. http://dx.doi.org/10.1016/j.cub.2006.02.005.

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Mulung, Bibi Rawiyah, and Andino Maseleno. "Proposed SMART Traffic Control Signal in Brunei Darussalam." TELKOMNIKA Indonesian Journal of Electrical Engineering 15, no. 2 (2015): 277. http://dx.doi.org/10.11591/tijee.v15i2.1540.

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Abstract (sommario):
This paper presents proposed SMART (Systematic Monitoring of Arterial Road Traffic Signals) traffic control signal in Brunei Darussalam. Traffic congestion due to stops and delays at traffic light signals has much been complained about in Brunei Darussalam as well as across the world during the recent years. There are primarily two types of traffic signal controls in Brunei Darussalam. The most common one is the fixed or pre-timed signal operation traffic light and the other one is the actuated signal operation traffic light. Although the actuated signal control is more efficient than the fixe
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Pan, Fuquan, Lixia Zhang, Changxi Ma, et al. "Impact of Vehicular Countdown Signals on Driving Psychologies and Behaviors: Taking China as an Example." Journal of Advanced Transportation 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/5838520.

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Countdown signal control is a relatively new control mode that can inform a driver in advance about the remaining time to pass through intersections or the time needed to wait for other drivers and pedestrians. At present, few countries apply vehicular countdown signals. However, in China, some cities have applied vehicular countdown signals for years, though it is unclear how and how much such signals influence driving psychologies and behaviors compared with non-countdown signal controls. The present work aims to clarify the impact of vehicular countdown signals on driving psychologies and b
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Zhao, Lin. "Numerical Control Lathe Cutting Force Signal On-Line Monitoring Design." Applied Mechanics and Materials 711 (December 2014): 329–32. http://dx.doi.org/10.4028/www.scientific.net/amm.711.329.

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The main research direction of Numerical control lathe cutting force signal on-line monitoring is to process real-time monitoring, using the sensor, charge amplifier, video acquisition card and computer to collect data and signal. Signal acquisition makes use of the piezoelectric sensor signals and send them to the computer in order to acquire the real-time data and display the dynamic signal so that monitor the process. Signal processing is the course that data will be collected for subsequent processing and analyzing. It includes display, filtering, correlation analysis, spectral analysis, e
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Polushin, P. A., O. R. Nikitin, and I. R. Dubov. "Quasioptimal control in diversed signal transmission." IOP Conference Series: Materials Science and Engineering 1227, no. 1 (2022): 012003. http://dx.doi.org/10.1088/1757-899x/1227/1/012003.

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Abstract To increase the noise immunity of signal transmission, diversity methods are now widely used, consisting in obtaining and combining several copies of the transmitted signal. In this case, it is possible to perform a combination either before the detection procedure or after it. If you do not take into account the possible use of non-linear types of modulation, then the pre-detector combination always has advantages over the post-detector combination. However, taking into account the nonlinear properties of the transmitted signals, new possibilities appear for increasing the noise immu
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R, Prof Lakshmi. "Literature Survey on Smart Ambulance Traffic Control System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31380.

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This study introduces a Smart Traffic Signal Control System designed to streamline ambulance transit through congested urban areas. Integrating RFID, GPS, and LTE technologies, this system establishes a direct link between ambulances and traffic signals, enabling prioritized passage for emergency vehicles. GPS tracking triggers real- time signal adjustments as ambulances approach intersections, granting immediate green signals through cloud-based communication. RFID confirms passage, while predictive algorithms optimize upcoming signal timings based on ambulance speed and estimated arrival, ef
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Tesi sul tema "CONTROL SIGNAL"

1

Renfrew, David T. "TRAFFIC SIGNAL CONTROL WITH ANT COLONY OPTIMIZATION." DigitalCommons@CalPoly, 2009. https://digitalcommons.calpoly.edu/theses/190.

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Abstract (sommario):
Traffic signal control is an effective way to improve the efficiency of traffic networks and reduce users’ delays. Ant Colony Optimization (ACO) is a metaheuristic based on the behavior of ant colonies searching for food. ACO has successfully been used to solve many NP-hard combinatorial optimization problems and its stochastic and decentralized nature fits well with traffic flow networks. This thesis investigates the application of ACO to minimize user delay at traffic intersections. Computer simulation results show that this new approach outperforms conventional fully actuated control under
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Zhang, Yihua. "An Evaluation of Transit signal Priority and SCOOT Adaptive Signal control." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/33051.

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Cities worldwide are faced with the challenge of improving transit service in urban areas using lower cost means. Transit signal priority is considered to be one of the most effective ways to improve the service of transit vehicles. Transit signal priority has become a very popular topic in transportation in the past 20 to 30 years and it has been implemented in many places around the world. In this thesis, transit signal priority strategies are categorized and an extensive literature review on past research on transit signal priority is conducted. Then a case study on Columbia Pike in Arling
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Al-Mudhaffar, Azhar. "Impacts of Traffic Signal Control Strategies." Doctoral thesis, Stockholm : Division of transports and logistics, Royal Institute of Technology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4268.

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Niittymäki, Jarkko. "Fuzzy traffic signal control principles and applications /." Espoo, Finland : Helsinki University of Technology, 2002. http://lib.hut.fi/Diss/2002/isbn9512257017/isbn9512257017.pdf.

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Dissertation for the degree of Doctor of Science in Technology--Helsinki University of Technology, Espoo, 2002.<br>"ISSN 0781-5816." Includes bibliographical references (p. 65-71). Available online as a PDF file via the World Wide Web.
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Yung, Sheung Kai. "Signal processing in local sensor validation." Thesis, University of Oxford, 1992. https://ora.ox.ac.uk/objects/uuid:974f513e-a556-4503-bae8-91460f10d3e3.

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Abstract (sommario):
Sensor integrity plays a crucial role in automatic control and system monitoring, both in achieving performance and guaranteeing safety. Conventional approaches in sensor failure detection demand precise process models and abundant central computing power. This thesis describes the development and the evaluation of a novel local sensor validation scheme which is independent of the underlying process and is applicable to a wide variety of sensors. A signal-based in-situ sensor validation scheme is proposed. Typical sensor failures are classified according to their signal patterns. To avoid the
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Nunes, Catarina Sofia da Costa. "Advanced signal processing and control in anaesthesia." Thesis, University of Sheffield, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.251478.

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Coeymans-Avaria, Juan Enrique. "Traffic signal systems in a developing country." Thesis, University of Southampton, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305939.

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Cadet, Gerard Nivard. "Traffic signal control - a neural network approach." FIU Digital Commons, 1996. http://digitalcommons.fiu.edu/etd/1963.

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Abstract (sommario):
Artificial Neural Networks (ANNs) have been proven to be an important development in a variety of problem solving areas. Increasing research activity in ANN applications has been accompanied by equally rapid growth in the commercial mainstream use of ANNs. However, there is relatively little research of practical application of ANNs taking place in the field of transportation engineering. The central idea of this thesis is to use Artificial Neural Network Software Autonet in connection with Highway Capacity Software to estimate delay. Currently existing signal control system are briefly discus
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Allee, Susan J. "Neuroendocrine control of a dynamic communication signal." FIU Digital Commons, 2007. http://digitalcommons.fiu.edu/etd/1093.

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Abstract (sommario):
Multiple physiological systems regulate the electric communication signal of the weakly electric gymnotiform fish, Brachyhypopomuspinnicaudatus. Fish were injected with neuroendocrine probes which identified pharmacologically relevant serotonin (5-HT) receptors similar to the mammalian 5-HT1AR and 5-HT2AR. Peptide hormones of the hypothalamic-pituitary-adrenal/interrenal axis also augment the electric waveform. These results indicate that the central serotonergic system interacts with the hypothalamic-pituitaryinterrenal system to regulate communication signals in this species. The same neuroe
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Wang, Qichao. "Street Traffic Signal Optimal Control for NEMA Controllers." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/101552.

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Abstract (sommario):
This dissertation aims to reduce urban traffic congestion with street traffic signal control. The traffic signal controllers in the U.S. follow the National Electrical Manufacturing Association Standards (NEMA Standards). In a NEMA controller, the control parameters for a coordinated control are cycle, green splits, and offset. This dissertation proposed a virtual phase-link concept and developed a macroscopic model to describe the dynamics of a traffic network. The coordinated optimal splits control problem was solved using model predictive control. The outputs of the solution are the green s
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Libri sul tema "CONTROL SIGNAL"

1

Godfrey, Keith, and Peter Jones, eds. Signal Processing for Control. Springer-Verlag, 1986. http://dx.doi.org/10.1007/bfb0008182.

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Keith, Godfrey, and Jones P. Dr, eds. Signal processing for control. Springer-Verlag, 1986.

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Herbert, Hanselmann, ed. Digital signal processors in control. IEEE, 1994.

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B, Ottersten, Söderström Torsten, and Wahlberg B, eds. Statistical signal processing and control. Pergamon, 1994.

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5

1942-, Katayama Tohru, and Sugimoto Sueo 1946-, eds. Statistical methods in control and signal processing. M. Dekker, 1997.

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Denney, Richard W. Signal timing under saturated conditions. U.S. Dept. of Transportation, Federal Highway Administration, Office of Operations, 2008.

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Åström, K. J., G. C. Goodwin, and P. R. Kumar, eds. Adaptive Control, Filtering, and Signal Processing. Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4419-8568-2.

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Paulraj, Arogyaswami, Vwani Roychowdhury, and Charles D. Schaper, eds. Communications, Computation, Control, and Signal Processing. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6281-8.

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1934-, Åström Karl J., Goodwin Graham C. 1945-, and Kumar P. R, eds. Adaptive control, filtering, and signal processing. Springer-Verlag, 1995.

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10

Nekoogar, Farzad. Digital control using digital signal processing. Prentice Hall, 1999.

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Capitoli di libri sul tema "CONTROL SIGNAL"

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Salter, R. J. "Signal control strategies." In Highway Traffic Analysis and Design. Macmillan Education UK, 1996. http://dx.doi.org/10.1007/978-1-349-13423-6_32.

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Salter, R. J. "Signal control strategies." In Highway Traffic Analysis and Design. Macmillan Education UK, 1989. http://dx.doi.org/10.1007/978-1-349-20014-6_32.

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Abramovici, Alex, and Jake Chapsky. "Multiple Signal Paths." In Feedback Control Systems. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4345-9_7.

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Oringel, Robert S. "Audio Signal Processing." In Audio Control Handbook. Routledge, 2023. http://dx.doi.org/10.4324/9781032632117-3.

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Albertos, Pedro, and Iven Mareels. "Signal Analysis." In Feedback and Control for Everyone. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-03446-6_4.

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Francis, Bruce. "Snippets of H ∞ Control Theory." In Signal Processing. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4684-7095-6_4.

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Cai, Guowei, Ben M. Chen, and Tong Heng Lee. "Measurement Signal Enhancement." In Advances in Industrial Control. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-635-1_5.

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Emelyanov, Stanislav V., and Sergey K. Korovin. "Signal Differentiation." In Control of Complex and Uncertain Systems. Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0771-2_10.

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Lovely, D. F. "Signals and Signal Processing for Myoelectric Control." In Powered Upper Limb Prostheses. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18812-1_3.

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Williamson, Darrell. "Signal Processing." In Advanced Textbooks in Control and Signal Processing. Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0541-1_4.

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Atti di convegni sul tema "CONTROL SIGNAL"

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Yamalova, Diana, and Torbjörn Wigren. "Control Signal Switching in Constrained Control of Averages." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10886543.

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D S, Pavan, Ronak R. Jain, Tirthankar Karmakar, and Chaitra N. "Density-Based Traffic Signal Control System." In 2025 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE). IEEE, 2025. https://doi.org/10.1109/iitcee64140.2025.10915480.

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Sheng, Liu Tian, Afizan Bin Azman, Navid Ali Khan, Siva Raja Sindiramutty, Suresh Singh, and Sahil Verma. "Reinforcement learning-based traffic signal control." In 2024 International Conference on Emerging Trends in Networks and Computer Communications (ETNCC). IEEE, 2024. https://doi.org/10.1109/etncc63262.2024.10767501.

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T, Kalai Selvi, Ajaykannan R, Boomika M, Jeevitha C, and Dinesh R. "AI-based Dynamic Traffic Signal Control." In 2025 5th International Conference on Pervasive Computing and Social Networking (ICPCSN). IEEE, 2025. https://doi.org/10.1109/icpcsn65854.2025.11035294.

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Liang, Shuo, and Fei Yan. "Iterative Fault-Tolerant Control Strategy for Urban Traffic Signals Under Signal Light Failure." In 2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2024. http://dx.doi.org/10.1109/ddcls61622.2024.10606774.

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Li, Nan, and Guangzhou Zhao. "Adaptive signal control for urban traffic network gridlock." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737520.

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McDonnell, Mark D. "Signal Estimation Via Averaging of Coarsely Quantised Signals." In 2007 Information, Decision and Control. IEEE, 2007. http://dx.doi.org/10.1109/idc.2007.374533.

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Ferreira, Jose Gregorio, and Tadeusz Sobczyk. "Multicriteria diagnosis of synchronous machines — Rotor-mounted sensing system. Rotor signal collector construction." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915182.

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Wu, Jia, Abdeljalil Abbas-Turki, Aurelien Correia, and Abdellah El Moudni. "Discrete Intersection Signal Control." In 2007 IEEE International Conference on Service Operations and Logistics, and Informatics. IEEE, 2007. http://dx.doi.org/10.1109/soli.2007.4383891.

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Biryukova, O. V., and I. V. Koretskaya. "Signal Recording System Control." In 2021 Systems of Signals Generating and Processing in the Field of on Board Communications. IEEE, 2021. http://dx.doi.org/10.1109/ieeeconf51389.2021.9415997.

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Rapporti di organizzazioni sul tema "CONTROL SIGNAL"

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Lafferriere, Gerardo. Traffic Signal Consensus Control. Transportation Research and Education Center (TREC), 2019. http://dx.doi.org/10.15760/trec.213.

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Lafferriere, Gerardo. Traffic Signal Consensus Control. Transportation Research and Education Center (TREC), 2019. http://dx.doi.org/10.15760/trec.221.

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Ramamoorthy, P. A. Intelligent Signal Processing for Active Control. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada252232.

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Chory, Joanne. Signal Transduction Pathways of Chloroplast Quality Control. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1416021.

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Pinto, J. G. Signal Processing Device to Control Microwave Output. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada216931.

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Chory, Joanne, and Jesse Woodson. Signal Transduction Pathways of Chloroplast Quality Control. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2001291.

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Willsky, Alan S. Challenges to Control in Signal Processing and Communications. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada459630.

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Benekohal, Rahim, Hongjae Jeon, Jesus Osorio, and Behnoush Garshasebi. Evaluation of Adaptive Signal Control Technology—Final Report. Illinois Center for Transportation, 2019. http://dx.doi.org/10.36501/0197-9191/19-007.

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Kothuri, Sirishi, Andrew Kading, Andrew Schrope, Kelly White, Edward Smaglik, and William Gil. Addressing Bicycle-Vehicle Conflicts with Alternate Signal Control Strategies. Transportation Research and Education Center, 2018. http://dx.doi.org/10.15760/trec.194.

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Pinsky, Mark A. Markov Processes Applied to Control, Replacement, and Signal Analysis. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada190563.

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