Дисертації з теми "Memory (Artificial)"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся з топ-50 дисертацій для дослідження на тему "Memory (Artificial)".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Переглядайте дисертації для різних дисциплін та оформлюйте правильно вашу бібліографію.
Hedberg, Charlie Forsberg, and Alexander Pedersen. "Artificial Intelligence : Memory-driven decisions in games." Thesis, Blekinge Tekniska Högskola, Institutionen för teknik och estetik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3640.
Повний текст джерелаAtt utveckla AI (Artificiell Intelligence) i spel kan vara en hård och utmanande uppgift. Ibland är det önskvärt att skapa beteenden som följer något sorts logiskt mönster. För att kunna göra detta måste information samlas in och processas. I detta kandidatarbete presenteras en algoritm som kan assistera nuvarande AI-teknologier för att samla in och memorera omgivningsinformation. Denna uppsats täcker också riktlinjer för praktisk implementering fastställda genom undersökning och tester.
Detta är en reflekstionsdel till en digital medieproduktion.
Bachhav, Pramod. "Explicit memory inclusion for efficient artificial bandwidth extension." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS492.
Повний текст джерелаMost ABE algorithms exploit contextual information or memory captured via the use of static or dynamic features extracted from neighbouring speech frames. The use of memory leads to higher dimensional features and increased computational complexity. When information from look-ahead frames is also utilised, then latency also increases. Past work points toward the benefit to ABE of exploiting memory in the form of dynamic features with a standard regression model. Even so, the literature is missing a quantitative analysis of the relative benefit of explicit memory inclusion. The research presented in this thesis assesses the degree to which explicit memory is of benefit and furthermore reports a number of different techniques that allow for its inclusion without significant increases to latency and computational complexity. Benefits are shown through both a quantitative analysis with an information-theoretic measure and subjective listening tests. Key contributions relate to the preservation of computational efficiency through the use of dimensionality reduction in the form of principal component analysis, semisupervised stacked autoencoders and conditional variational auto-encoders. The two latter techniques optimise dimensionality reduction to deliver superior ABE performance
Kanar, Ege. "Photography as artificial memory: Construction of the Photographic Self." Master's thesis, Akademie múzických umění v Praze. Filmová a televizní fakulta AMU. Knihovna, 2008. http://www.nusl.cz/ntk/nusl-78095.
Повний текст джерелаMoposita, Tatiana. "Artificial Neural Network (ANN) design using Compute-in-Memory." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS682.
Повний текст джерелаNowadays, the era of ”More than Moore” has arisen as a significant influence in light of the limitations anticipated by Moore’s law. The computing systems are exploring alternative technologies to sustain and enhance performance improvements. The idea of alternative innovative technologies has emerged in solving challenges of electronic systems inspired by biological neural networks, commonly referred to as Artificial Neural Network (ANN). The use of emerging non-volatile memory (eNVM) technologies are being explored as promising alternatives. These technologies offer several advantages over traditional CMOS technology, such as increased speed, higher densities, and lower power consumption. As a result, Compute-in-memory employs eNVMs to perform computation within the memory itself, hence increasing memory capacity and processing speed. The objective of this thesis focuses on the research of Artificial Neural Networks design using Compute in Memory, by employing efficient hardware solutions for ANNs at both circuit- and architecture-level. Recent research work in this context has proposed very efficient circuit designs to optimize the enormous computational needs required by data processing by ANNs. Therefore, to explore the capabilities of an ANN at the output node, the design of activation functions were proposed. The selection of an activation function is significant as it determines the power and capabilities of the neural network, and the accuracy of predictions is primarily dependent on this choice. To assess the effectiveness of an activation function designed for analog implementation, the sigmoid and the softmax activation function are proposed. Besides, this thesis explores the integration of emerging memory devices like Spin-Transfer-Torque Magnetic Random Access Memory (STT-MRAM) with CMOS technology. This combined approach aims to leverage the intrinsic capability of in-memory computing offered by these devices. STT-MRAMs based on state-of-the-art perpendicular magnetic tunneling junction (MTJ) and FinFETs has been considered for this study. Single-barrier magnetic tunnel junction (SMTJ) and double-barrier magnetic tunnel junction (DMTJ) devices are considered to evaluate the impact of STT-MRAM cell based on DMTJ against the conventional SMTJ counterpart on the performance of a two-layer multilayer perceptron (MLP) neural network. The assessment was carried out through a customized simulation framework from device and bitcell levels to memory architecture and algorithm levels. Moreover, to improve the energy-efficiency of a Logic-in-Memory (LIM) architecture based on STT-MTJ devices, a new architecture (SIMPLY+) from the Smart Material Implication (SIMPLY) logic and perpendicular MTJ based STT-MRAM technologies was developed. The SIMPLY+ scheme is a promising solution for the development of energy-efficient and reliable in-memory computing architectures. All circuit solutions were evaluated using commercial circuit simulators (e.g. Cadence Virtuoso). Circuit design activity involving emerging memory devices also required the use and calibration of Verilog-A based compact models to integrate the behavior of such devices into the circuit design tool. The solutions presented in this thesis involve techniques that offer significant advancements for future applications. From a design perspective, the integration of logic modules with STT-MRAM memory is highly feasible due to the seamless compatibility between STT-MRAMs and CMOS circuits. This approach not only proves advantageous for standard CMOS technology but also leverages the potential of emerging technologies
Day, Jonathan. ""Must I remember?" : artificial memory systems and early modern England." Thesis, University of Liverpool, 2014. http://livrepository.liverpool.ac.uk/2006202/.
Повний текст джерелаLudwig, Lars [Verfasser], and Thomas [Akademischer Betreuer] Lachmann. "Extended Artificial Memory. Toward an integral cognitive theory of memory and technology / Lars Ludwig. Betreuer: Thomas Lachmann." Kaiserslautern : Technische Universität Kaiserslautern, 2013. http://d-nb.info/1045194794/34.
Повний текст джерелаNtourntoufis, Panayotis. "Aspects of the theory of weightless artificial neural networks." Thesis, Imperial College London, 1994. http://hdl.handle.net/10044/1/8506.
Повний текст джерелаTurvey, Simon Paul. "Analysing and enhancing the performance of associative memory architectures." Thesis, University of Hertfordshire, 2003. http://hdl.handle.net/2299/14113.
Повний текст джерелаTigreat, Philippe. "Sparsity, redundancy and robustness in artificial neural networks for learning and memory." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0046/document.
Повний текст джерелаThe objective of research in Artificial Intelligence (AI) is to reproduce human cognitive abilities by means of modern computers. The results of the last few years seem to announce a technological revolution that could profoundly change society. We focus our interest on two fundamental cognitive aspects, learning and memory. Associative memories offer the possibility to store information elements and to retrieve them using a sub-part of their content, thus mimicking human memory. Deep Learning allows to transition from an analog perception of the outside world to a sparse and more compact representation.In Chapter 2, we present a neural associative memory model inspired by Willshaw networks, with constrained connectivity. This brings an performance improvement in message retrieval and a more efficient storage of information.In Chapter 3, a convolutional architecture was applied on a task of reading partially displayed words under similar conditions as in a former psychology study on human subjects. This experiment put inevidence the similarities in behavior of the network with the human subjects regarding various properties of the display of words.Chapter 4 introduces a new method for representing categories usingneuron assemblies in deep networks. For problems with a large number of classes, this allows to reduce significantly the dimensions of a network.Chapter 5 describes a method for interfacing deep unsupervised networks with clique-based associative memories
Church, Dana L. "Spatial encoding of artificial flowers by bumblebees (Bombus impatiens): The contents of memory." Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/29206.
Повний текст джерелаHeyder, Jakob. "Hierarchical Temporal Memory Software Agent : In the light of general artificial intelligence criteria." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-75868.
Повний текст джерелаHågbäck, Moa. "Artificially Authentic and Authentically Artificial : Experiencing the body of the past through the affect of the transmedial narrative of the Outlander-story world." Thesis, Linnéuniversitetet, Institutionen för kulturvetenskaper (KV), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-86157.
Повний текст джерелаBrogliato, Marcelo Salhab. "Understanding the critical distance in sparse distributed memory." reponame:Repositório Institucional do FGV, 2012. http://hdl.handle.net/10438/13095.
Повний текст джерелаApproved for entry into archive by ÁUREA CORRÊA DA FONSECA CORRÊA DA FONSECA (aurea.fonseca@fgv.br) on 2015-01-06T12:52:32Z (GMT) No. of bitstreams: 1 !FullThesis-v6 -biblioteca-digital.pdf: 64255589 bytes, checksum: 0ca16d02e6d615b8fc4c6f4f46db2c22 (MD5)
Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2015-01-12T12:15:58Z (GMT) No. of bitstreams: 1 !FullThesis-v6 -biblioteca-digital.pdf: 64255589 bytes, checksum: 0ca16d02e6d615b8fc4c6f4f46db2c22 (MD5)
Made available in DSpace on 2015-01-12T12:16:51Z (GMT). No. of bitstreams: 1 !FullThesis-v6 -biblioteca-digital.pdf: 64255589 bytes, checksum: 0ca16d02e6d615b8fc4c6f4f46db2c22 (MD5) Previous issue date: 2012-02-02
Modelos de tomada de decisão necessitam refletir os aspectos da psi- cologia humana. Com este objetivo, este trabalho é baseado na Sparse Distributed Memory (SDM), um modelo psicologicamente e neuro- cientificamente plausível da memória humana, publicado por Pentti Kanerva, em 1988. O modelo de Kanerva possui um ponto crítico: um item de memória aquém deste ponto é rapidamente encontrado, e items além do ponto crítico não o são. Kanerva calculou este ponto para um caso especial com um seleto conjunto de parâmetros (fixos). Neste trabalho estendemos o conhecimento deste ponto crítico, através de simulações computacionais, e analisamos o comportamento desta 'Critical Distance' sob diferentes cenários: em diferentes dimensões; em diferentes números de items armazenados na memória; e em diferentes números de armazenamento do item. Também é derivada uma função que, quando minimizada, determina o valor da 'Critical Distance' de acordo com o estado da memória. Um objetivo secundário do trabalho é apresentar a SDM de forma simples e intuitiva para que pesquisadores de outras áreas possam imaginar como ela pode ajudá-los a entender e a resolver seus problemas.
Models of decision-making need to reflect human psychology. Towards this end, this work is based on Sparse Distributed Memory (SDM), a psychologically and neuroscientifically plausible model of human memory, published by Pentti Kanerva in 1988. Kanerva‘s model of memory holds a critical point: prior to this point, a previously stored item can be easily retrieved; but beyond this point an item cannot be retrieved. Kanerva has methodically calculated this point for a particu- lar set of (fixed) parameters. Here we extend this knowledge, through computational simulations, in which we analyzed this critical point behavior under several scenarios: in several dimensions, in number of stored items in memory, and in number of times the item has been rehearsed. We also derive a function that, when minimized, determines the value of critical distance according to the state of the memory. A secondary goal is to present the SDM in a simple and intuitive way in order that researchers of other areas can think how SDM can help them to understand and solve their problems.
Wecke, Liliane. "Cardiac memory studies in two human models /." Stockholm, 2006. http://diss.kib.ki.se/2006/91-7140-614-X/.
Повний текст джерелаBambeck, Timothy J. "A computer controlled data acquisition and control system for a shape-memory alloy artificial muscle." Ohio : Ohio University, 1993. http://www.ohiolink.edu/etd/view.cgi?ohiou1174935244.
Повний текст джерелаNarayanan, Pavanesh. "Sensor-less Control of Shape Memory Alloy Using Artificial Neural Network and Variable Structure Controller." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1416501021.
Повний текст джерелаStone, Erik E. Skubic Marge. "Adaptive temporal difference learning of spatial memory in the water maze task." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/6586.
Повний текст джерелаHelman, Shaun. "The knowledge and processing underlying the structural mere exposure effect." Thesis, University of Reading, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314322.
Повний текст джерелаTadesse, Yonas Tegegn. "Creating Human-Like Facial Expressions Utilizing Artificial Muscles and Skin." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/30159.
Повний текст джерелаPh. D.
Hirtzlin, Tifenn. "Digital Implementation of Neuromorphic systems using Emerging Memory devices." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPAST071.
Повний текст джерелаWhile electronics has prospered inexorably for several decades, its leading source of progress will stop in the next coming years, due to the fundamental technological limits of transistors. Nevertheless, microelectronics is currently offering a major breakthrough: in recent years, memory technologies have undergone incredible progress, opening the way for multiple research venues in embedded systems. Additionally, a major feature for future years will be the ability to integrate different technologies on the same chip. new emerging memory devices that can be embedded in the core of the CMOS, such as Resistive Random Access Memory (RRAM) or Spin Torque Magnetic Tunnel Junction (STMRAM) based on naturally intelligent inmemory-computing architecture. Three braininspired algorithms are carefully examined: Bayesian reasoning binarized neural networks, and an approach that further exploits the intrinsic behavior of components, population coding of neurons. Each of these approaches explores different aspects of in-memory computing
Ehrich, John Fitzgerald. "The effects of L1 orthography on processing an artificial logographic script." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/35768/1/John_Fitzgerald_Ehrich_Thesis.pdf.
Повний текст джерелаKianzad, Soheil. "A treatise on highly twisted artificial muscle : thermally driven shape memory alloy yarn and coiled nylon actuators." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54782.
Повний текст джерелаApplied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
Holmes, Andrew J. "The use of non-volatile a-Si:H memory devices for synaptic weight storage in artificial neural networks." Thesis, University of Edinburgh, 1995. http://hdl.handle.net/1842/14085.
Повний текст джерелаReese, Caitlin S. "The Implicit Artificial Grammar Task: Preliminary Evaluation of its Potential for Detection of Noncredible Effort/Malingering." Ohio University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1406763394.
Повний текст джерелаElvir, Miguel. "EPISODIC MEMORY MODEL FOR EMBODIED CONVERSATIONAL AGENTS." Master's thesis, University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3000.
Повний текст джерелаM.S.Cp.E.
School of Electrical Engineering and Computer Science
Engineering and Computer Science
Computer Engineering MSCpE
Lindell, Adam. "Pulse Repetition Interval Time Series Modeling for Radar Waves using Long Short-Term Memory Artificial Recurrent Neural Networks." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-377865.
Повний текст джерелаBhalala, Smita Ashesh 1966. "Modified Newton's method for supervised training of dynamical neural networks for applications in associative memory and nonlinear identification problems." Thesis, The University of Arizona, 1991. http://hdl.handle.net/10150/277969.
Повний текст джерелаLongela, Makusudi Simon. "The development of an artificial hand using nickel-titanium as actuators." Thesis, Cape Peninsula University of Technology, 2013. http://hdl.handle.net/20.500.11838/2229.
Повний текст джерелаThis thesis outlines a proposed mechanical design, prototyping and testing of a five fingered artificial hand made of 15 articulated joints actuated by Shape Memory Alloys (SMAs) mimicking muscular functions. SMAs Artificial muscles were incorporated in the forearm and artificial tendons made of nylon wires passing through a hollow palm transmit the pulling force to bend the fingers. Torsion springs set in each joint of the fingers create enough restoring force to straighten the finger when the actuators are disengaged. Nickel-Titanium (NiTi) wires were intrinsically embedded within the hand structure allowing significant movements mimicking human hand-like gestures. A control box made of switches connected to the artificial hand helps to control each gesture. A modular approach was taken in the design to facilitate the manufacture and assembly processes. Nickel-Titanium wires were used as actuators to perform the artificial muscle functions by changing their crystallographic structures due to Joule's heating. Rapid prototyping techniques were employed to manufacture the hand in ABS plastic.
Francis, Anthony G. Jr. "Context-sensitive asynchronous memory : a general experience-based method for managing information access in cognitive agents." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/9177.
Повний текст джерелаBonnet, Djohan. "Synaptic uncertainty for in-memory computing." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST037.
Повний текст джерелаThe high demand for Artificial Neural Networks, combined with their high energy cost due to the memory bottleneck of von-Neumann architectures, has intensified efforts to overcome hardware constraints. This thesis explores the interdisciplinary field of neuromorphic computing, focusing on experimental studies, algorithms, and integrated circuit design. The experimental part investigates the electrical characteristics of resistive random access memories based on metal-oxide transition (OxRAMs) and phase change memories (PCMs) to understand their different variabilities. Additionally, a Bayesian neural network is implemented across 75 electronic chips. Moving to algorithms, the research involves both experimental and theoretical analyses of a novel learning method named MESU, which stands for metaplasticity from synaptic uncertainty. This method exploits synaptic uncertainty in Bayesian neural networks for continual learning. Lastly, for the circuit design part, a full custom in-memory computing demonstrator is developed, leveraging OxRAM technology, covering aspects from transistor sizing to layout realization
Bazzi, Hussein. "Resistive memory co-design in CMOS technologies." Electronic Thesis or Diss., Aix-Marseille, 2020. http://www.theses.fr/2020AIXM0567.
Повний текст джерелаMany diversified applications (internet of things, embedded systems for automotive and medical applications, artificial intelligence) require an integrated circuit (SoC, System on Chip) with high-performance non-volatile memories to operate optimally. Although Flash memory is widely used today, this technology needs high voltage for programing operations and has reliability issues that are hard to handle beyond 18 nm technological node, increasing the cost of circuit design and fabrication. In this context, the semiconductor industry seeks an alternative non-volatile memory that can replace Flash memories. Among possible candidates (MRAM - Magnetic Random Access Memory, PCM - Phase Change Memory, FeRAM - Ferroelectric Random Access Memory), Resistive memories (RRAMs) offer superior performances on essential key points: compatibility with CMOS manufacturing processes, scalability, current consumption (standby and active), operational speed. Due to its relatively simple structure, RRAM technology can be easily integrated in any design flow opening the way for the development of new architectures that answer Von Neumann bottleneck. In this thesis, the main object is to show the integration abilities of RRAM devices with CMOS technology, using circuit design and electrical measurements, in order to develop different hybrid structures: non-volatile Static Random Access Memories (SRAM), True Random Number Generator (TRNG) and artificial neural networks
Forslund, John, and Jesper Fahlén. "Predicting customer purchase behavior within Telecom : How Artificial Intelligence can be collaborated into marketing efforts." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279575.
Повний текст джерелаDenna studie undersöker implementeringen av en AI-modell som förutspår kunders köp, inom telekombranschen. Studien syftar även till att påvisa hur en sådan AI-modell kan understödja beslutsfattande i marknadsföringsstrategier. Genom att designa AI-modellen med en Recurrent Neural Network (RNN) arkitektur med ett Long Short-Term Memory (LSTM) lager, drar studien slutsatsen att en sådan design möjliggör en framgångsrik implementering med tillfredsställande modellprestation. Instruktioner erhålls stegvis för att konstruera modellen i studiens metodikavsnitt. RNN-LSTM-modellen kan med fördel användas som ett hjälpande verktyg till marknadsförare för att bedöma hur en kunds beteendemönster på en hemsida påverkar deras köpbeteende över tiden, på ett kvantitativt sätt - genom att observera det ramverk som författarna kallar för Kundköpbenägenhetsresan, på engelska Customer Purchase Propensity Journey (CPPJ). Den empiriska grunden av CPPJ kan hjälpa organisationer att förbättra allokeringen av marknadsföringsresurser, samt gynna deras digitala närvaro genom att möjliggöra mer relevant personalisering i kundupplevelsen.
Hellman, James. ""As Mind to the Body": Prudence and Artificial Memory in the Illustrations and Commentary of George Sandys' Ovid's Metamorphosis Englished (1632)." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/506.
Повний текст джерелаEndo, Yoichiro. "Countering Murphys law the use of anticipation and improvisation via an episodic memory in support of intelligent robot behavior /." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26466.
Повний текст джерелаCommittee Chair: Arkin, Ronald; Committee Member: Balch, Tucker; Committee Member: Dellaert, Frank; Committee Member: Potter, Steve; Committee Member: Ram, Ashwin. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Price, Ryan William. "Hierarchical Temporal Memory Cortical Learning Algorithm for Pattern Recognition on Multi-core Architectures." PDXScholar, 2011. https://pdxscholar.library.pdx.edu/open_access_etds/202.
Повний текст джерелаSalihoglu, Utku. "Toward a brain-like memory with recurrent neural networks." Doctoral thesis, Universite Libre de Bruxelles, 2009. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210221.
Повний текст джерела
Based on these assumptions, this thesis provides a computer model of neural network simulation of a brain-like memory. It first shows experimentally that the more information is to be stored in robust cyclic attractors, the more chaos appears as a regime in the background, erratically itinerating among brief appearances of these attractors. Chaos does not appear to be the cause, but the consequence of the learning. However, it appears as an helpful consequence that widens the network’s encoding capacity. To learn the information to be stored, two supervised iterative Hebbian learning algorithm are proposed. One leaves the semantics of the attractors to be associated with the feeding data unprescribed, while the other defines it a priori. Both algorithms show good results, even though the first one is more robust and has a greater storing capacity. Using these promising results, a biologically plausible alternative to these algorithms is proposed using cell assemblies as substrate for information. Even though this is not new, the mechanisms underlying their formation are poorly understood and, so far, there are no biologically plausible algorithms that can explain how external stimuli can be online stored in cell assemblies. This thesis provide such a solution combining a fast Hebbian/anti-Hebbian learning of the network's recurrent connections for the creation of new cell assemblies, and a slower feedback signal which stabilizes the cell assemblies by learning the feed forward input connections. This last mechanism is inspired by the retroaxonal hypothesis.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
Mustafa, Hassan M., and Ayoub Al-Hamadi. "On Teaching Quality Improvement of a Mathematical Topic Using Artificial Neural Networks Modeling (With a Case Study)." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-80718.
Повний текст джерелаJüngel, Matthias. "The memory-based paradigm for vision-based robot localization." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://dx.doi.org/10.18452/16593.
Повний текст джерелаFor autonomous mobile robots, a solid world model is an important prerequisite for decision making. Current state estimation techniques are based on Hidden Markov Models and Bayesian filtering. These methods estimate the state of the world (belief) in an iterative manner. Data obtained from perceptions and actions is accumulated in the belief which can be represented parametrically (like in Kalman filters) or non-parametrically (like in particle filters). When the sensor''s information gain is low, as in the case of bearing-only measurements, the representation of the belief can be challenging. For instance, a Kalman filter''s Gaussian models might not be sufficient or a particle filter might need an unreasonable number of particles. In this thesis, I introduce a new state estimation method which doesn''t accumulate information in a belief. Instead, perceptions and actions are stored in a memory. Based on this, the state is calculated when needed. The system has a particular advantage when processing sparse information. This thesis presents how the memory-based technique can be applied to examples from RoboCup (autonomous robots play soccer). In experiments, it is shown how four-legged and humanoid robots can localize themselves very precisely on a soccer field. The localization is based on bearings to objects obtained from digital images. This thesis presents a new technique to recognize field lines which doesn''t need any pre-run calibration and also works when the field lines are partly concealed and affected by shadows.
Musunuru, Venkata Krishna Kanth. "Virtuo-ITS: An Interactive Tutoring System to Teach Virtual Memory Concepts of an Operating System." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1495481049986755.
Повний текст джерелаNeto, Camilo Rodrigues. "Propriedades de recuperação de memória em redes neurais atratoras." Universidade de São Paulo, 1997. http://www.teses.usp.br/teses/disponiveis/76/76131/tde-31102008-173551/.
Повний текст джерелаAttractor neural networks are feedback neural networks with no pre-defined connection structure. These types of neural networks present a rich dissipative dynamics and, in general, are used as associative memory devices. Such devices have the capacity to retrieve a previously stored memory, even when exposed to partial or degraded information. To store a memory means to create an attractor for it in the network dynamics, and this is done by specifying the set of synaptic weighs. In this thesis, we concentrate on two classical ways of specifying the synaptics weighs: the pseudo-inverse and the optimal weighs models. For extremely diluted neural networks, for which the connectivity C and the number of neurons N satisfy the condition C « In N, we obtain the phase diagrams in the complete space of the model parameters through the analytical study of the retrieval overlap dynamics. We also investigate the retrieval properties of fully connected neural networks using two approaches: the analytical study of the neighborhood of the stored patterns, and the exhaustive enumeration of the attractors via numerical simulations. Finally, we study analytically the problem of categorization in the pseudo-inverse model. Categorization in attractor neural networks is the capacity to create an attractor for a concept to which the network has had access only through a finite number of examples.
Samikwa, Eric. "Flood Prediction System Using IoT and Artificial Neural Networks with Edge Computing." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280299.
Повний текст джерелаÖversvämningar drabbar miljontals människor över hela världen genom att orsaka dödsfall och förstöra egendom. Sakernas Internet (IoT) har använts i områden som översvämnings förutsägelse, översvämnings övervakning, översvämning upptäckt, etc. Även om IoT-teknologier inte kan stoppa förekomsten av översvämningar, så är de mycket användbara när det kommer till transport av katastrofberedskap och motverkande handlingsdata. Utveckling har skett när det kommer till att förutspå översvämningar med hjälp av artificiella neuronnät (ANN). Trots de olika framstegen inom system för att förutspå översvämningar genom ANN, så har det varit mindre fokus på användningen av edge computing vilket skulle kunna förbättra effektivitet och tillförlitlighet. I detta examensarbete föreslås ett system för kortsiktig översvämningsförutsägelse genom IoT och ANN, där gissningsberäkningen utförs över en låg effekt edge enhet. Systemet övervakar sensordata från regn och vattennivå i realtid och förutspår översvämningsvattennivåer i förtid genom att använda långt korttidsminne. Systemet kan köras på batteri eftersom det använder låg effekt IoT-enheter och kommunikationsteknik. Resultaten från en utvärdering av en prototyp av systemet indikerar en bra prestanda när det kommer till noggrannhet att förutspå översvämningar och responstid. Användningen av ANN med edge computing kommer att förbättra effektiviteten av tidiga varningssystem för översvämningar i realtid genom att ta gissningsberäkningen närmare till där datan samlas.
Comiran, Mariane. "Toxidez por cobre: reflexos na qualidade de sementes e no desenvolvimento inicial de aveia preta." Universidade Federal de Santa Maria, 2017. http://repositorio.ufsm.br/handle/1/11623.
Повний текст джерелаin the soill elevated over the years through anthropogenic actions such as the application of manure and cupping fungicides. As a reflection of these increases the establishment and development of plants grown in these environments can be limited and compromised. Considering the particularities of the different species in resisting and completing their cycle on these conditions this work aimed to evaluate Cu interference on the establishment and initial growth of black oats. The treatments were set up in 5x2 bifactorial, with five concentrations of copper (0, 60, 120, 180, 240 μM) and two sub lots (vigor levels). Thus, analyzes of physiological parameters of black oat seedlings and plants from two sub lots, one artificially aged and another not, both originated from a single lot, were performed. Two experiments were carried out; in the first one, physiological parameters were evaluated which comprise the establishment capacity of the seedlings such as the first count and germination test in B.O.D germinator with controlled conditions; the second one consisted in hydroponic plant cultivation and evaluated physiological parameters of growth, such as length and dry mass of shoot and root, and length and total dry mass. A completely randomized design was adopted in both experiments, being the second one in a split-split plot arrangement. Cu concentrations did not affect seedling establishment capacity, on the other hand the vigor of the seed sub lot affected this ability, with more vigorous (not aged) seeds sub lot having a better establishment. Cu concentrations were detrimental to the initial growth of black oat plants above 60 μM independent of sub lot studied. Seedlings from the non-aged sub lot (high vigor) presented higher initial growth than those from the aged sub lot (low vigor), however acclimatization in the hydroponic system equaled them in root growth and caused an inversion in the total plant growth, being this higher in low vigor sub lot plants.
O cobre (Cu) está entre os metais cujos teores em solo foram elevados ao longo dos anos em decorrência de ações antrópicas como a aplicação de dejetos de animas e fungicidas cúpricos. Como reflexo destes aumentos o estabelecimento e o desenvolvimento das plantas cultivadas nestes ambientes pode ser limitado e comprometido. Consideradas as particularidades das diferentes espécies em resistirem e completarem seu ciclo sobre estas condições pretendeu-se com este trabalho avaliar a interferência do Cu sobre o estabelecimento e crescimento inicial da aveia preta. Os tratamentos foram configurados em bifatorial 5x2, com cinco concentrações de cobre (0, 60, 120, 180, 240 μM) e dois sublotes (níveis de vigor). Nesse sentido, foram realizadas análises dos parâmetros fisiológicos de plântulas e plantas de aveia preta de dois sublotes de sementes, um envelhecido e outro não envelhecido, ambos originados de um único lote. Foram realizados dois experimentos; o primeiro, avaliou parâmetros fisiológicos que compreendem a capacidade de estabelecimento das plântulas, através dos testes de primeira contagem e germinação de sementes em germinador tipo BOD com condições controladas; o segundo experimento, consistiu do cultivo de plantas em sistema hidropônico e avaliou parâmetros fisiológicos de crescimento, como o comprimento e a massa seca de parte aérea e raiz, e comprimento e massa seca total. Foi adotado delineamento inteiramente casualizado em ambos os experimentos, sendo o segundo experimento com arranjo experimental em parcela sub subdividida. As concentrações de Cu não afetaram a capacidade de estabelecimento de plântulas, por outro lado o vigor do sublote de sementes afetou esta capacidade, sendo que melhor estabelecimento foi observado no sublote não envelhecido (alto vigor). O crescimento inicial de plantas de aveia preta foi influenciado negativamente por concentrações de Cu superiores a 60 μM independente do sublote em estudo. Plântulas oriundas do sublote não envelhecido (alto vigor) apresentaram crescimento inicial superior as oriundas do sublote envelhecido (baixo vigor), entretanto a aclimatação em sistema hidropônico as igualou em crescimento de raiz e ocasionou uma inversão no crescimento total da planta, sendo este superior em plantas do sublote de baixo vigor.
Vaughan, Renata Aparecida da Rocha. "Avaliação das funções executivas em portadores de fibrilação atrial e insuficiência cardíaca." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/5/5142/tde-30012018-105412/.
Повний текст джерелаIntroduction: Heart Failure (HF) and Atrial Fibrillation (AF) are frequent pathologies in the elderly population and are associated with cognitive disorders. However, its consequences on executive functions, which are responsible for solving problems, have not yet been fully clarified. Objective: to investigate the characteristics of executive functioning in patients with AF and/or HF and to identify if such functioning is comparable to that of a control group. Methods: A cross-sectional observational study performed in a tertiary care hospital in cardiology, which evaluated 191 subjects with a mean age of 69.1 years (min.: 60, Max.: 82) distributed in five different groups: AF, with HF associated with AF, with HF and controls (with and without pacemaker). The groups were matched by age group and socio-demographic variables, submitted to neuropsychological evaluation and statistical analysis involved non-parametric tests (Kruskall-Wallys and Mann-Whitney), Pearson\'s chi-square and Fisher\'s exact test. Results: In subjects with AF compared to non-pacemaker controls, we observed statistically significant differences related to operational memory (p = 0.034), late memory (p = 0.015), semantic memory and verbal fluency (p < 0.001), comprehension P < 0.001), visuospatial planning and ability (p < 0.001), visual perception and language (p < 0.001) and inhibitory control and processing speed in the three phases of the instrument (p < 0.008; p < 0.004, p < 0.002). In subjects with HF associated with HF, the observed differences involved: semantic memory and verbal fluency (p = 0.05), planning and visuospatial ability (p < 0.001), visual perception and language (p < 0.001) and inhibitory control and processing speed (p = 0.002, p < 0.001, p = 0.145, respectively). Subjects with HF demonstrated the same performance of the group of individuals with AF and HF, with differences related to the same functions, except in the first phase of the instrument that evaluated inhibitory control and processing speed (p < 0.001). Regarding functionality, we did not observe a statistically significant difference between groups. Conclusions: The executive functioning of individuals with AF or IC is not comparable to that of individuals without these diseases. AF, from a neuropsychological perspective, intensifies the damage of FE and memory
Pacheco, Renato Ferrari. "Módulos neurais para modelagem de falsas memórias." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-12052017-103355/.
Повний текст джерелаFalse memories are a kind of memory failure, in which the subject may (a) recognize as known an never seen object or never happened fact or (b) don\'t recognize something that was already presented him. These are false memories and wrong rejections. According to false memory theory, two parallel processes act during memorization and recognition, one on verbatim information and other on gist information. In this work is proposed a artificial neural network model system that takes in account these two processes, functional issues about brain structures involved on memorization and the an information flow analog to the occurred in the brain. The neural model is validated by training to store in recover lists of semantically related words. In the model and representation scheme formulation, phonological and semantic informations were used intending to simulate brain computations and results of human subjects experiments. In such experiment, 12 lists of something about 15 semantically related words, are heard and, in the second step, in the sequence, many of these words, other related words and not related words are heard in a recognition test, when subjets say if that word was or was not heard during memorization steps. Results obtained from computer tests are very close of human results, and the produced model may be used as a tool for analysis of the influences of the many processes that take place during memorization and recognition.
Huang, Yiming. "Phoneme Recognition Using Neural Network and Sequence Learning Model." Ohio University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1236027180.
Повний текст джерелаAbrishami, Hedayat. "Deep Learning Based Electrocardiogram Delineation." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1563525992210273.
Повний текст джерелаFiguerola, Wilfredo Blanco. "Din?mica da Plasticidade Sin?ptica em neur?nios do hipocampo durante ciclos de sono: um estudo computacional." Universidade Federal do Rio Grande do Norte, 2012. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15187.
Повний текст джерелаCoordena??o de Aperfei?oamento de Pessoal de N?vel Superior
Several research lines show that sleep favors memory consolidation and learning. It has been proposed that the cognitive role of sleep is derived from a global scaling of synaptic weights, able to homeostatically restore the ability to learn new things, erasing memories overnight. This phenomenon is typical of slow-wave sleep (SWS) and characterized by non-Hebbian mechanisms, i.e., mechanisms independent of synchronous neuronal activity. Another view holds that sleep also triggers the specific enhancement of synaptic connections, carrying out the embossing of certain mnemonic traces within a lattice of synaptic weights rescaled each night. Such an embossing is understood as the combination of Hebbian and non-Hebbian mechanisms, capable of increasing and decreasing respectively the synaptic weights in complementary circuits, leading to selective memory improvement and a restructuring of synaptic configuration (SC) that can be crucial for the generation of new behaviors ( insights ). The empirical findings indicate that initiation of Hebbian plasticity during sleep occurs in the transition of the SWS to the stage of rapid eye movement (REM), possibly due to the significant differences between the firing rates regimes of the stages and the up-regulation of factors involved in longterm synaptic plasticity. In this study the theories of homeostasis and embossing were compared using an artificial neural network (ANN) fed with action potentials recorded in the hippocampus of rats during the sleep-wake cycle. In the simulation in which the ANN did not apply the long-term plasticity mechanisms during sleep (SWS-transition REM), the synaptic weights distribution was re-scaled inexorably, for its mean value proportional to the input firing rate, erasing the synaptic weights pattern that had been established initially. In contrast, when the long-term plasticity is modeled during the transition SWSREM, an increase of synaptic weights were observed in the range of initial/low values, redistributing effectively the weights in a way to reinforce a subset of synapses over time. The results suggest that a positive regulation coming from the long-term plasticity can completely change the role of sleep: its absence leads to forgetting; its presence leads to a positive mnemonic change
Diversas linhas de pesquisa demonstram que o sono favorece a consolida??o de mem?rias e o aprendizado. Tem sido proposto que o papel cognitivo do sono deriva de um redimensionamento global dos pesos sin?pticos, capaz de restabelecer homeostaticamente a capacidade de aprender coisas novas, apagando mem?rias durante a noite. Tal fen?meno seria t?pico do sono de ondas lentas ( slow wave sleep , SWS) e caracterizado por mecanismos n?o-Hebbianos, isto ?, independentes da atividade neuronal sincr?nica. Outra abordagem postula que o sono desencadeia tamb?m um realce de conex?es sin?pticas espec?ficas, levando a um entalhamento de certos tra?os mnem?nicos no ?mbito de uma matriz de pesos sin?pticos redimensionados a cada noite. Tal entalhamento ? entendido como a combina??o de mecanismos Hebbianos e n?o-Hebbianos, capazes respectivamente de aumentar e diminuir os pesos sin?pticos em circuitos complementares, levando ? melhoria seletiva de mem?rias e a uma reestrutura??o da configura??o sin?ptica ( synaptic configuration , SC) que pode ser crucial para a gera??o de novos comportamentos ( insights ). Os achados emp?ricos indicam que a indu??o de plasticidade Hebbiana durante o sono acontece na transi??o do SWS para o est?gio de movimento r?pido dos olhos ( rapid eye movement , REM), possivelmente devido ?s grandes diferen?as entre os regimes das taxas de disparos entre os estados e ? regula??o positiva de fatores envolvidos na plasticidade sin?ptica de longo prazo. Neste estudo, as teorias da homeostase e do entalhamento foram comparadas usando uma rede neural artificial ( artificial neural network , ANN) alimentada com potenciais de a??o registrados no hipocampo de ratos durante todo o ciclo sono-vig?lia. Na simula??o em que a ANN n?o aplicou mecanismos de plasticidade de longo prazo durante o sono (transi??o SWS-REM), a distribui??o pesos sin?pticos foram inexoravelmente re-escalada para uma media proporcional ? taxa de disparo das entradas, apagando eventualmente o padr?o de pesos sin?pticos inicialmente estabelecido. Em contraste, quando a plasticidade de longo prazo foi modelada durante a transi??o SWS-REM, o aumento dos pesos sin?pticos foi observado em toda a gama de valores iniciais, efetivamente redistribuindo os pesos de modo a refor?ar um subconjunto de sinapses ao longo do tempo. Os resultados sugerem que uma regula??o positiva proveniente da plasticidade de longo prazo pode alterar completamente o papel do sono: sua aus?ncia leva ao esquecimento, sua presen?a leva a uma mudan?a mnem?nica positiva
Elwér, Åsa. "Learning by Liking- a Mere Exposure Version of the AGL Paradigm." Thesis, Linköping University, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2075.
Повний текст джерелаThe artificial grammar learning (AGL) paradigm has been intensively researched since the 60-s. In general, these investigations attempt to study the implicit acquisition of structural regularities. Among other things, it has been suggested that the AGL paradigm can serve as a model for the process of acquiring a natural language. Thus it can serve as a well-controlled laboratory task that might be used to understand certain aspects of the process of language acquisition. For example the AGL paradigm has been used in an attempt to isolate the acquisition of syntactic aspects of language. Several experimental studies show that the participants acquire knowledge of the underlying rule system since they are able to differentiate grammatical strings from non-grammatical ones. It has been argued that the traditionally conducted AGL paradigm with grammaticality instructions might make the task explicit, at least during the test phase. In order to imitate the language learning process as close as possible, to rule out the possibility of an explicit component during the testing phase (i.e., keeping the retrieval process implicit) and to rule out explicit rule conformity or rule following, we modified the classical AGL paradigm. In a behavioural study we combined the AGL paradigm with an altered mere exposure paradigm in an attempt to better model aspects of language acquisition. We were able to show that subjects, classifying under mere exposure instructions, categorize grammatical and non-grammatical strings just as well as those solving the classification task with the grammaticality instructions. This indicates that the mere exposure version might serve as a more appropriate model for language acquisition.
Lawrie, Sofía. "Information representation and processing in neuronal networks: from biological to artificial systems and from first to second-order statistics." Doctoral thesis, Universitat Pompeu Fabra, 2022. http://hdl.handle.net/10803/673989.
Повний текст джерелаLas redes neuronales se presentan hoy, hipotéticamente, como las responsables de las capacidades computacionales de los sistemas nerviosos biológicos. De la misma manera, los sistemas neuronales artificiales son intensamente explotados en una diversidad de aplicaciones industriales y científicas. No obstante, cómo la información es representada y procesada por estas redes está aún sujeto a debate. Es decir, no está claro qué propiedades de la actividad neuronal son útiles para llevar a cabo computaciones. En esta tesis, presento un conjunto de resultados que relaciona el primer orden estadístico de la actividad neuronal con comportamiento, en el contexto general de codificación/decodificación, para analizar datos recolectados mientras primates no humanos realizaban una tarea de memoria de trabajo. Subsecuentemente, voy más allá del primer orden y muestro que las estadísticas de segundo orden en computación de reservorios, un modelo de red neuronal artificial y recurrente, constituyen un candidato robusto para la representación y transmisión de información con el fin de clasificar señales multidimensionales.
Freire, Ananda Lima. "A DimensÃo temporal no projeto de classificadores de padrÃes para navegaÃÃo de robÃs mÃveis: um estudo de caso." Universidade Federal do CearÃ, 2009. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=16223.
Повний текст джерелаEste trabalho investiga o grau de influÃncia que a inclusÃo de mecanismos de memÃria de curta duraÃÃo (MCD) exercem sobre o desempenho de classificadores neurais quando aplicados em tarefas de navegaÃÃo de robÃs. Em particular, trata da navegaÃÃo do tipo Wall Following. Para este fim, quatro conhecidas arquiteturas neurais (Perceptron LogÃstico, Perceptron Multicamadas, Mistura de Especialistas e rede de Elman) sÃo usadas com o intuito de associar diferentes padrÃes de leituras sensoriais com quatro classes de aÃÃes prÃ-determinadas. Todas as etapas dos experimentos - aquisiÃÃo dos dados, seleÃÃo e treinamento das arquiteturas em simulador, alÃm da execuÃÃo das mesmas em robà mÃvel real (SCITOS G5) - sÃo escritas em detalhes. Os resultados obtidos sugerem que a tarefa de seguir paredes, formulada como um problema de classificaÃÃo de padrÃes, à nÃo-linearmente separÃvel, resultado este que favorece a rede MLP quando os classificadores sÃo treinados sem MCD. Contudo, se mecanismos de MCD sÃo usados, entÃo atà mesmo uma rede linear à capaz de executar a tarefa de interesse com sucesso
This work reports results of an investigation on the degree of influence that the inclusion of short-term memory mechanisms has on the performance of neural classifiers when applied to robot navigation tasks. In particular, we deal with the well-known strategy of navigating by âwall-followingâ. For this purpose, four neural architectures (Logistic Perceptron, Multilayer Perceptron, Mixture of Experts and Elman network) are used to associate different sensory input patterns with four predetermined action categories. All stages of the experiments - data acquisition, selection and training of the architectures in a simulator and their execution on a real mobile robot - are described. The obtained results suggest that the wall-following task, formulated as a pattern classification problem, is nonlinearly separable, a result that favors the MLP network if no memory of input patterns are taken into account. If short-term memory mechanisms are used, then even a linear network is able to perform the same task successfully