Дисертації з теми "Estimation de l'horizon mobile"
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Ranjbar, Gigasari Roza. "Model Predictive Controller for large-scale systems - Application to water networks." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Lille Douai, 2024. http://www.theses.fr/2024MTLD0002.
Повний текст джерелаThis thesis addresses the challenge of optimizing the management of canals, a complex task due to their extensive scale and distinctive attributes, including intricate dynamics, considerable time delays, and minimal bottom slopes. Specifically, the central goal is to ensure the navigability of the network, which involves maintaining safe water levels for vessel travel, through control theory. More precisely, the water levels must remain within a predefined range around a setpoint. Additionally, typical aims encompass reducing operational costs and enhancing the equipment’s life expectancy. In this regard, another objective in the management of such networks is replacing the possible sensors across canals by applying a moving robot to take the required measurements. To accomplish effective management, it becomes imperative to ensure efficient control over hydraulic structures such as gates, pumps, and locks. To this end, a control algorithm is introduced based on an existing model derived from the Saint-Venant equations. The modeling approach simplified the original complex description providing adaptability and facilitating the systematic integration of both current and delayed information. However, the resulting model formulation falls within the category of delayed descriptor systems, necessitating extensions to standard control and state estimation tools. Model predictive control and moving horizon estimation methods can be readily tailored for this formulation, while also adapting physical and operational constraints seamlessly. Given the extensive nature of canals, an evaluation of the digital twin was untaken to address the critical need for advanced tools in the management of such networks. By harnessing the capabilities of digital twins, we aimed to enhance our understanding of canal dynamics, past scenarios, and management strategies. This evaluation sought to bridge the gap between theory and practical implementation, offering a tangible means to playback past events, test diverse management approaches, and ultimately equip decision-makers with robust criteria for informed and effective network management.The methodologies presented above are applied to a practical case study, a canal in the northern region of France. The objective is to validate the efficacy of these approaches in a real-world context.While centralized MPC provides resilience through its receding-horizon approach, its deterministic nature limits its ability to systematically address uncertainties. To effectively tackle these system uncertainties, the implementation of Stochastic MPC (SMPC) has been adopted. SMPC integrates probabilistic descriptions into control design, offering a methodical approach to accommodating uncertainties. In this context, the application of SMPC is interconnected with a mobile robot aimed at replacing existing sensors along the canal to capture measurements. Consequently, a part of this thesis focuses on the design of SMPC in conjunction with a mobile robot. This approach has been applied to an ASCE Test canal to evaluate its effectiveness
Poquin, Didier. "Estimation de la verticale subjective en tangage : contribution de l'horizon visuel apparent." Grenoble 2, 1998. http://www.theses.fr/1998GRE29016.
Повний текст джерелаThe factors determining spatial orientation in the median plane have been relatively neglected, although this dimension is the preferential plane of human displacements and the alert reaction in case of danger. Concerning pitch orientation, the observers point of view is an essential factor to estimate the surface slant. In this frame, the hypothesis according to pitch visually perceived vertical (pitch VPV) is assessed from visually perceived eye level (VPEL) has been assumed. It has been asked to an observer, seated in a dark room, to assess the subjective vertical by adjusting to the gravity direction a luminous and rectangular surface (the rod), and in other hand to judge the eye level by setting a luminous target in the horizontal plane getting through his eyes. The first part of results shows that the pitch VPV assessments have its own mechanisms whose the main factors are the geometrical cues relative to the form of the rod and the subjective eye level. Those factors could explain the lack of correlation observed between roll and pitch rod adjustments to the gravity direction and the systematic deviation of the pitch VPV, 'top of the rod toward the observer'. The second part of results describes two processes involving the VPEL to estimate the pitch VPV. The first processes, called 'mechanism of cenfered orthogonalisation', leads to adjust the rod perpendicular to an imaginary line getting through the center of the surface to the subjective eye level. This process occurs when VPEL errors are small. The second mechanism, called 'mechanism of surcompensation', is observed when the subject believes that the rod is put up or down relative to his perceived eye level. The consequence is a erroned compensation from this subjective point of view. This mechanism occurs when VPEL errors are large. The last experimental section confirms, with a visual scene, the existence of mechanisms of centered orthogonalisation or surcompensation to adjust a rod to the gravity direction in the median plane. In conclusion, the subjective eye level is considered as the point of view from which an observer calculates the slant orientation of planar surfaces. In other words, the determination of the pitch orientation of an object initially needs the estimation of the observer's localization in the environment
Patel, Chirag S. "Channel modeling and estimation for mobile-to-mobile OFDM communications." Thesis, Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/13552.
Повний текст джерелаAlli, Idd Pazi. "Channel estimation in mobile wireless systems." Thesis, KTH, Signalbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-98754.
Повний текст джерелаAngladon, Vincent. "Room layout estimation on mobile devices." Phd thesis, Toulouse, INPT, 2018. http://oatao.univ-toulouse.fr/20745/1/ANGLADON_Vincent.pdf.
Повний текст джерелаKleynhans, Waldo. "On channel estimation for mobile WiMAX." Diss., Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-01262009-102433/.
Повний текст джерелаKasebzadeh, Parinaz. "Parameter Estimation for Mobile Positioning Applications." Licentiate thesis, Linköpings universitet, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-141877.
Повний текст джерелаNing, Yu. "Mobile speed estimation for hierarchical wireless network." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4298.
Повний текст джерелаThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (July 14, 2006) Includes bibliographical references.
Zhou, Bin. "Mobile velocity estimation in multipath fading channels." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0005/MQ42710.pdf.
Повний текст джерелаThiagarajan, Arvind. "Probabilistic models for mobile phone trajectory estimation." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68497.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (p. 157-161).
This dissertation is concerned with the problem of determining the track or trajectory of a mobile device - for example, a sequence of road segments on an outdoor map, or a sequence of rooms visited inside a building - in an energy-efficient and accurate manner. GPS, the dominant positioning technology today, has two major limitations. First, it consumes significant power on mobile phones, making it impractical for continuous monitoring. Second, it does not work indoors. This dissertation develops two ways to address these limitations: (a) subsampling GPS to save energy, and (b) using alternatives to GPS such as WiFi localization, cellular localization, and inertial sensing (with the accelerometer and gyroscope) that consume less energy and work indoors. The key challenge is to match a sequence of infrequent (from sub-sampling) and inaccurate (from WiFi, cellular or inertial sensing) position samples to an accurate output trajectory. This dissertation presents three systems, all using probabilistic models, to accomplish this matching. The first, VTrack, uses Hidden Markov Models to match noisy or sparsely sampled geographic (lat, lon) coordinates to a sequence of road segments on a map. We evaluate VTrack on 800 drive hours of GPS and WiFi localization data collected from 25 taxicabs in Boston. We find that VTrack tolerates significant noise and outages in location estimates, and saves energy, while providing accurate enough trajectories for applications like travel-time aware route planning. CTrack improves on VTrack with a Markov Model that uses "soft" information in the form of raw WiFi or cellular signal strengths, rather than geographic coordinates. It also uses movement and turn "hints" from the accelerometer and compass to improve accuracy. We implement CTrack on Android phones, and evaluate it on cellular signal data from over 126 (1,074 miles) hours of driving data. CTrack can retrieve over 75% of a user's drive accurately on average, even from highly inaccurate (175 metres raw position error) GSM data. iTrack uses a particle filter to combine inertial sensing data from the accelerometer and gyroscope with WiFi signals and accurately track a mobile phone indoors. iTrack has been implemented on the iPhone, and can track a user to within less than a metre when walking with the phone in the hand or pants pocket, over 5 x more accurately than existing WiFi localization approaches. iTrack also requires very little manual effort for training, unlike existing localization systems that require a user to visit hundreds or thousands of locations in a building and mark them on a map.
by Arvind Thiagarajan.
Ph.D.
Thomas, Nicholas J. "Techniques for mobile location estimation in UMTS." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/426.
Повний текст джерелаRovinelli, Marco. "Realtime Monocular Depth Estimation on Mobile Phones." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24159/.
Повний текст джерелаTurbillon, Céline. "Estimation et prévision des processus Moyenne Mobile fonctionnels." Paris 6, 2007. http://www.theses.fr/2007PA066379.
Повний текст джерелаAzemi, Ghasem. "Mobile velocity estimation using a time-frequency approach." Thesis, Queensland University of Technology, 2003. https://eprints.qut.edu.au/15807/1/Ghasem_Azemi_Thesis.pdf.
Повний текст джерелаAzemi, Ghasem. "Mobile Velocity Estimation Using a Time-Frequency Approach." Queensland University of Technology, 2003. http://eprints.qut.edu.au/15807/.
Повний текст джерелаChan, Ka Chun. "A dual channel location estimation system for mobile computing." HKBU Institutional Repository, 2003. http://repository.hkbu.edu.hk/etd_ra/445.
Повний текст джерелаWard, Christopher Charles. "Terrain sensing and estimation for dynamic outdoor mobile robots." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42419.
Повний текст джерелаIncludes bibliographical references (p. 120-125).
In many applications, mobile robots are required to travel on outdoor terrain at high speed. Compared to traditional low-speed, laboratory-based robots, outdoor scenarios pose increased perception and mobility challenges which must be considered to achieve high performance. Additionally, high-speed driving produces dynamic robot-terrain interactions which are normally negligible in low speed driving. This thesis presents algorithms for estimating wheel slip and detecting robot immobilization on outdoor terrain, and for estimating traversed terrain profile and classifying terrain type. Both sets of algorithms utilize common onboard sensors. Two methods are presented for robot immobilization detection. The first method utilizes a dynamic vehicle model to estimate robot velocity and explicitly estimate longitudinal wheel slip. The vehicle model utilizes a novel simplified tire traction/braking force model in addition to estimating external resistive disturbance forces acting on the robot. The dynamic model is combined with sensor measurements in an extended Kalman filter framework. A preliminary algorithm for adapting the tire model parameters is presented. The second, model-free method takes a signal recognition-based approach to analyze inertial measurements to detect robot immobilization. Both approaches are experimentally validated on a robotic platform traveling on a variety of outdoor terrains. Two detector fusion techniques are proposed and experimentally validated which combine multiple detectors to increase detection speed and accuracy. An algorithm is presented to classify outdoor terrain for high-speed mobile robots using a suspension mounted accelerometer. The algorithm utilizes a dynamic vehicle model to estimate the terrain profile and classifies the terrain based on spatial frequency components of the estimated profile. The classification algorithm is validated using experimental results collected with a commercial automobile driving in real-world conditions.
by Christopher Charles Ward.
S.M.
Kang, Shinwoo 1976. "Terrain parameter estimation and traversability assessment for mobile robots." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/42830.
Повний текст джерелаIncludes bibliographical references (leaves 65-68).
The estimation of terrain characteristics is an important missions of Martian exploration rovers. Since only limited resources and human supervision are available, efficient and autonomous method of estimation are required. In this thesis, an on-line estimation method of two important terrain parameters, cohesion and internal friction angle, is developed. The method uses onboard rover sensors and is computationally efficient. Terrain parameter estimation is of scientific interest, and can also be useful in predicting rover mobility on rough-terrain. A method to estimate traversability of a rover on deformable terrain using on-board sensors is presented. Simulation and experimental results show that the proposed methods can accurately and efficiently estimate traversability of deformable terrain.
by Shinwoo Kang.
S.M.
Nordlander, Rickard. "Pose Estimation in an Outdoors Augmented Reality Mobile Application." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-70653.
Повний текст джерелаMolitor, Torsten, and Hilding Wollbo. "Estimation of Statistical Properties in a Mobile MIMO System." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239375.
Повний текст джерелаPatel, Chirag S. "Wireless channel modeling, simulation, and estimation." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-03282006-200818/.
Повний текст джерелаAndrew, Alfred, Committee Member ; Durgin, Gregory, Committee Member ; Li, Geoffrey, Committee Member ; Ingram, Mary Ann, Committee Member ; Stuber, Gordon, Committee Chair.
Saur, Stephan. "Channel estimation for mobile wideband code division multiple access (WCDMA)." Aachen Shaker, 2008. http://d-nb.info/989680819/04.
Повний текст джерелаJohansson, Oscar. "Weight Estimation and Evaluation of User Suggestions in Mobile Browsing." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-154647.
Повний текст джерелаKumar, Sumeet Ph D. Massachusetts Institute of Technology. "Mobile sensor systems for field estimation and "hot spot" identification." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/87977.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (pages 155-166).
Robust, low-cost mobile sensing enables effective monitoring and management of urban environment and infrastructure which contributes towards a sustainable future. While mobile sensor systems have attracted significant attention in recent years, a large scale deployment for urban infrastructure monitoring poses many research challenges. One fundamental challenge is dealing with noisy and uncontrolled samples stemming from both noisy sensor measurements and locations, and lack of control on sensor deployment. Such conditions pose difficulties in field estimation and "hot spot" identification from sensor data. My thesis contributions aim to bridge this gap. In this thesis, I designed and developed a mobile sensor system for urban light infrastructure monitoring and studied two problems on field estimation in the presence of noisy and uncontrolled samples with general implications on mobile sensing. As an example system, I designed and successfully tested a city-wide street light scanning mobile sensor platform. Currently, street light maintenance uses labor-intensive, poorly scalable manual inspection techniques. My system automatically maps street illumination levels and lamp infrastructure. The collected data presents challenges in identifying lamp "hot spots" from false positives and using sensor data from noisy sensor locations for estimating luminosity maps. I present an algorithm for identifying various light sources from video streams and combining that data with location information to geotag lamps. To identity the light sources, I developed a supervised classifier for lamp classification and later extended it to develop a method for estimating the height of the street lamps. As accurate car location information is critical for successful luminosity mapping, I discuss how I improved car location estimates by integrating multiple independent data streams such as vehicle speed data obtained via on-board diagnostic systems and GPS. Towards such field deployments, one must address fundamental challenges related to both hardware implementation and data analytics. In this thesis, I addressed two problems related to mobile sensor based sampling and signal estimation: nonuniform sampling and errors in sample location. Uniform grid sampling is often impractical in the context of mobile spatial sampling. As an alternative, I studied [delta]-dense sensor arrangements as a realistic scheme for non-uniform flexible sampling. To assess its utility, I derived sufficient conditions for estimating a signal represented in a finite-dimensional basis set and present simulation results on the numerical stability of signal estimation under [delta]-dense sampling. Furthermore, I present the use of proper orthogonal decomposition as a technique to obtain basis sets for signals that are solutions to a parametric differential equation. Finally, I studied how errors in the location measurements of mobile nodes affect the overall signal estimation problem. To address such signal estimation problems, I developed a computationally efficient iterative linear estimator and compared my approach to the state of the art expectation-maximization technique. I present simulation studies on the performance of the estimator and discuss results on its numerical stability. My approach offers several orders of magnitude reduction in computational time while achieving comparable mean squared estimation error to other techniques making it an appealing candidate for real-time embedded mobile sensing applications.
by Sumeet Kumar.
Ph. D.
Hughes, Lloyd Haydn. "Enhancing mobile camera pose estimation through the inclusion of sensors." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95917.
Повний текст джерелаENGLISH ABSTRACT: Monocular structure from motion (SfM) is a widely researched problem, however many of the existing approaches prove to be too computationally expensive for use on mobile devices. In this thesis we investigate how inertial sensors can be used to increase the performance of SfM algorithms on mobile devices. Making use of the low cost inertial sensors found on most mobile devices we design and implement an extended Kalman filter (EKF) to exploit their complementary nature, in order to produce an accurate estimate of the attitude of the device. We make use of a quaternion based system model in order to linearise the measurement stage of the EKF, thus reducing its computational complexity. We use this attitude estimate to enhance the feature tracking and camera localisation stages in our SfM pipeline. In order to perform feature tracking we implement a hybrid tracking algorithm which makes use of Harris corners and an approximate nearest neighbour search to reduce the search space for possible correspondences. We increase the robustness of this approach by using inertial information to compensate for inter-frame camera rotation. We further develop an efficient bundle adjustment algorithm which only optimises the pose of the previous three key frames and the 3D map points common between at least two of these frames. We implement an optimisation based localisation algorithm which makes use of our EKF attitude estimate and the tracked features, in order to estimate the pose of the device relative to the 3D map points. This optimisation is performed in two steps, the first of which optimises only the translation and the second optimises the full pose. We integrate the aforementioned three sub-systems into an inertial assisted pose estimation pipeline. We evaluate our algorithms with the use of datasets captured on the iPhone 5 in the presence of a Vicon motion capture system for ground truth data. We find that our EKF can estimate the device’s attitude with an average dynamic accuracy of ±5°. Furthermore, we find that the inclusion of sensors into the visual pose estimation pipeline can lead to improvements in terms of robustness and computational efficiency of the algorithms and are unlikely to negatively affect the accuracy of such a system. Even though we managed to reduce execution time dramatically, compared to typical existing techniques, our full system is found to still be too computationally expensive for real-time performance and currently runs at 3 frames per second, however the ever improving computational power of mobile devices and our described future work will lead to improved performance. From this study we conclude that inertial sensors make a valuable addition into a visual pose estimation pipeline implemented on a mobile device.
AFRIKAANSE OPSOMMING: Enkel-kamera struktuur-vanaf-beweging (structure from motion, SfM) is ’n bekende navorsingsprobleem, maar baie van die bestaande benaderings is te berekeningsintensief vir gebruik op mobiele toestelle. In hierdie tesis ondersoek ons hoe traagheidsensors gebruik kan word om die prestasie van SfM algoritmes op mobiele toestelle te verbeter. Om van die lae-koste traagheidsensors wat op meeste mobiele toestelle gevind word gebruik te maak, ontwerp en implementeer ons ’n uitgebreide Kalman filter (extended Kalman filter, EKF) om hul komplementêre geaardhede te ontgin, en sodoende ’n akkurate skatting van die toestel se postuur te verkry. Ons maak van ’n kwaternioon-gebaseerde stelselmodel gebruik om die meetstadium van die EKF te lineariseer, en so die berekeningskompleksiteit te verminder. Hierdie afskatting van die toestel se postuur word gebruik om die fases van kenmerkvolging en kameralokalisering in ons SfM proses te verbeter. Vir kenmerkvolging implementeer ons ’n hibriede volgingsalgoritme wat gebruik maak van Harris-hoekpunte en ’n benaderde naaste-buurpunt-soektog om die soekruimte vir moontlike ooreenstemmings te verklein. Ons verhoog die robuustheid van hierdie benadering, deur traagheidsinligting te gebruik om vir kamerarotasies tussen raampies te kompenseer. Verder ontwikkel ons ’n doeltreffende bondelaanpassingsalgoritme wat slegs optimeer oor die vorige drie sleutelraampies, en die 3D punte gemeenskaplik tussen minstens twee van hierdie raampies. Ons implementeer ’n optimeringsgebaseerde lokaliseringsalgoritme, wat gebruik maak van ons EKF se postuurafskatting en die gevolgde kenmerke, om die posisie en oriëntasie van die toestel relatief tot die 3D punte in die kaart af te skat. Die optimering word in twee stappe uitgevoer: eerstens net oor die kamera se translasie, en tweedens oor beide die translasie en rotasie. Ons integreer die bogenoemde drie sub-stelsels in ’n pyplyn vir postuurafskatting met behulp van traagheidsensors. Ons evalueer ons algoritmes met die gebruik van datastelle wat met ’n iPhone 5 opgeneem is, terwyl dit in die teenwoordigheid van ’n Vicon bewegingsvasleggingstelsel was (vir die gelyktydige opneming van korrekte postuurdata). Ons vind dat die EKF die toestel se postuur kan afskat met ’n gemiddelde dinamiese akkuraatheid van ±5°. Verder vind ons dat die insluiting van sensors in die visuele postuurafskattingspyplyn kan lei tot verbeterings in terme van die robuustheid en berekeningsdoeltreffendheid van die algoritmes, en dat dit waarskynlik nie die akkuraatheid van so ’n stelsel negatief beïnvloed nie. Al het ons die uitvoertyd drasties verminder (in vergelyking met tipiese bestaande tegnieke) is ons volledige stelsel steeds te berekeningsintensief vir intydse verwerking op ’n mobiele toestel en hardloop tans teen 3 raampies per sekonde. Die voortdurende verbetering van mobiele toestelle se berekeningskrag en die toekomstige werk wat ons beskryf sal egter lei tot ’n verbetering in prestasie. Uit hierdie studie kan ons aflei dat traagheidsensors ’n waardevolle toevoeging tot ’n visuele postuurafskattingspyplyn kan maak.
Lu, Bowen. "Bayesian estimation of environmental fields using mobile wireless sensor networks." Thesis, University of Essex, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.635987.
Повний текст джерелаSebastian, Bijo. "Traversability Estimation Techniques for Improved Navigation of Tracked Mobile Robots." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/94629.
Повний текст джерелаDoctor of Philosophy
This dissertation explores ways to improve autonomous navigation in unstructured terrain conditions, with specific applications to unmanned casualty extraction in disaster scenarios. Search and rescue applications often put the lives of first responders at risk. Using robotic systems for human rescue in disaster scenarios can keep first responders out of danger. To enable safe robotic casualty extraction, this dissertation proposes a novel rescue robot design concept named SAVER. The proposed design concept consists of several subsystems including a declining stretcher bed, head and neck support system, and robotic arms that conceptually enable safe casualty manipulation and extraction based on high-level commands issued by a remote operator. In order to enable autonomous navigation of the proposed conceptual system in challenging outdoor terrain conditions, this dissertation proposes improvements in planning, trajectory tracking control and terrain estimation. The proposed techniques are able to take into account the dynamic effects of robot-terrain interaction including slip experienced by the vehicle, slope of the terrain and actuator limitations. The proposed techniques have been validated through simulations and experiments in indoor and simple outdoor terrain conditions. The applicability of the above techniques in improving tele-operation of rescue robotic systems in unstructured terrain is also discussed at the end of this dissertation.
Wong, Hak Lim. "Signal strength-based location estimation in two different mobile networks." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/700.
Повний текст джерелаKan, Ka Ho. "Location estimation system based on the GSM network." HKBU Institutional Repository, 2004. http://repository.hkbu.edu.hk/etd_ra/524.
Повний текст джерелаChaplin, Bruce Alan. "Motion estimation from stereo image sequences for a mobile mapping system." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0020/MQ48058.pdf.
Повний текст джерелаAfgani, Mostafa Z. "Exploitation of signal information for mobile speed estimation and anomaly detection." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/4890.
Повний текст джерелаAhmadzadeh, Amir Masoud. "Capacity and Cell-Range Estimation for Multitraffic Users in Mobile WiMAX." Thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-19122.
Повний текст джерелаUppsatsnivå: D
Li, Wei. "Intelligent joint channel parameter estimation techniques for mobile wireless positioning applications." Thesis, Brunel University, 2010. http://bura.brunel.ac.uk/handle/2438/7764.
Повний текст джерелаKrumbein, Marc. "Heading Estimation of a Mobile Robot Using Multiple UWB Position Sensors." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1555001007552678.
Повний текст джерелаHåkansson, Dennis, and Johan Lövberg. "Development of algorithm for a mobile-based estimation of heart rate." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43561.
Повний текст джерелаGenom att utföra ett test av ens fysiska prestanda kan man utvärdera ens hälsostatus och upptäcka indikationer på avvikelser i kroppen. Syftet med detta arbete är att utveckla en mobilbaserad algoritm som kan beräkna och uppskatta ens puls när man utför the Queens College Step Test på begäran av Mobistudy. Mobistudy vill inkludera detta test i deras mobilapplikation som fokuserar på att kunna användas som ett verktyg inom forskning för att samla in data. Algoritmen använder sig av mobilens kamera för att samla in data från användarens finger och använder den insamlade data för att beräkna pulsen. Algoritmen testades först gentemot data som samlades in vid utvecklingsstadiet och resultatet visade på att genomsnittliga felet var under 5% samt att standardavvikelsen var under 3%. Två deltagare mellan åldern 20 och 25 utförde tre tester var utav the Queens College Step Test och resultatet visade att algoritmen var tillräckligt noggrann i sin uppskattning av pulsen efter ett utfört test.
Hsu, Pei-Lun. "Machine Learning-Based Data-Driven Traffic Flow Estimation from Mobile Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300712.
Повний текст джерелаInformation om trafikflödet är nödvändig för övervakning av fordonsutsläpp och trafikstyrning. Trafikflöden kan dock inte observeras överallt och när som helst på vägen på grund av höga installationskostnader och t.ex. funktionsstörningar hos stationära sensorer. För att kompensera för stationära sensorers svagheter analyseras i detta arbete ett tillvägagångssätt för att estimera trafikflöden från mobila data som tillhandahålls av INRIX. Detta kommersiella dataset innehåller restider som kommer från användare av bl.a. färdnavigatorer i fordon och som har en bred rumslig täckning och hög kvalitet. Idén är att utveckla modeller baserade på artificiellt neuronnät för att automatiskt extrahera samband mellan trafikflödesdata och restidsdata från INRIX-mätningarna baserat på historiska data och med hänsyn till tidsmässiga och rumsliga beroenden. Vi utförde experiment med fyra veckors data från INRIX och från stationära sensorer på två intilliggande vägsegment på E4:an i Stockholm. Modellerna valideras med hjälp av estimering av trafikflöde baserat på en veckas INRIX- data. Jämfört med det traditionella tillvägagångssättet som anpassar stationära samband mellan trafikflöde och hastighet baserat på fundamentaldiagram, förbättrar det nya tillvägagångssättet noggrannheten avsevärt. Dessutom visar resultaten att modellerna i den nya metoden bättre hanterar avvikelser i ingående variabler och kan öka noggrannheten på estimatet för vägsegmentet utan stationär sensor. Den nya metoden kan därför vara lämplig för att uppskatta trafikflöden på vägsegment närliggande en stationär sensor. Metodiken ger ett automatiserat sätt att bygga modeller som är anpassade till datamängderna och som förbättrar noggrannheten vid estimering av trafikflöden. Den kan också enkelt integrera nya datakällor. Metodiken är lämplig att tillämpa på tillämpningar inom intelligenta transportsystem för trafikövervakning och trafikstyrning.
Chu, Man Kin. "A hybrid approach for mobile location estimation in cellular radio networks." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/672.
Повний текст джерелаJayasinghe, Sankissa G. "Techniques of detection, estimation and coding for fading channels." Thesis, Loughborough University, 1989. https://dspace.lboro.ac.uk/2134/7282.
Повний текст джерелаFilliat, David. "Cartographie et estimation globale de la position pour un robot mobile autonome." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2001. http://tel.archives-ouvertes.fr/tel-00655469.
Повний текст джерелаSun, Xusheng. "Optimal distributed detection and estimation in static and mobile wireless sensor networks." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44825.
Повний текст джерелаDevaraj, Sreekalyan. "Estimation of path duration in mobile ad-hoc networks: A theoretical study." Thesis, Wichita State University, 2009. http://hdl.handle.net/10057/2529.
Повний текст джерелаThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
von, dem Knesebeck Matthias. "Fast motion estimation methods for H.264 video coding on mobile devices." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/28761.
Повний текст джерелаYiin, Lihbor. "Sequence estimation receivers for trellis-coded continuous phase modulation on mobile channels." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/14818.
Повний текст джерелаSaur, Stephan [Verfasser]. "Channel Estimation for Mobile Wideband Code Division Multiple Access (WCDMA) / Stephan Saur." Aachen : Shaker, 2008. http://d-nb.info/1162793139/34.
Повний текст джерелаSheen, Wern-Ho. "Performance analysis of sequence estimation techniques for intersymbol interference channels." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/13089.
Повний текст джерелаCoulton, Paul. "Novel synchronisation and channel estimation techniques using auxiliary decoding information." Thesis, Lancaster University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266675.
Повний текст джерелаMiao, H. (Honglei). "Channel estimation and positioning for multiple antenna systems." Doctoral thesis, University of Oulu, 2007. http://urn.fi/urn:isbn:9789514284113.
Повний текст джерелаMashali, Mustafa. "Kinematic Control of Redundant Mobile Manipulators." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5989.
Повний текст джерелаLenardi, Massimiliano. "Advanced mobile receivers and downlink channel estimation for 3G UMTS-FDD WCDMA systems /." [S.l.] : [s.n.], 2002. http://library.epfl.ch/theses/?nr=2574.
Повний текст джерелаSadeghi, Parastoo School of Electrical Engineering And Telecommunications UNSW. "Modelling, information capacity, and estimation of time-varying channels in mobile communication systems." Awarded by:University of New South Wales. School of Electrical Engineering And Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/32310.
Повний текст джерела