This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed.
A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron.
Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations.
A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of a linear filter, given the input of the filter encoded with the same neuron model.
Автор: Mandoiu Название: Bioinformatics Algorithms: Techniques and Applications ISBN: 0470097736 ISBN-13(EAN): 9780470097731 Издательство: Wiley Рейтинг: Цена: 24227.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Bioinformatics Algorithms: Techniques and Applications targets the future collaboration of researchers in algorithms, bioinformatics, and molecular biology. It addresses critical bioinformatics research areas of protein-protein interaction, molecular modeling in drug design, and structural biology.
Описание: Modelling and system identification.- Advanced control methods.- Signal processing for condition monitoring and fault diagnosis.- Applications.
Описание: Safety in industrial process and production plants is a concern of rising importance but because the control devices which are now exploited to improve the performance of industrial processes include both sophisticated digital system design techniques and complex hardware, there is a higher probability of failure.
Описание: This book presents the most important findings from the 9th International Conference on Modelling, Identification and Control (ICMIC’17), held in Kunming, China on July 10–12, 2017. It covers most aspects of modelling, identification, instrumentation, signal processing and control, with a particular focus on the applications of research in multi-agent systems, robotic systems, autonomous systems, complex systems, and renewable energy systems.The book gathers thirty comprehensively reviewed and extended contributions, which help to promote evolutionary computation, artificial intelligence, computation intelligence and soft computing techniques to enhance the safety, flexibility and efficiency of engineering systems. Taken together, they offer an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, mechanical engineering and communication engineering.
Описание: Algebraic Identification and Estimation Methods in Feedback Control Systems presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems.
Автор: Tohru Katayama Название: Subspace Methods for System Identification ISBN: 1849969884 ISBN-13(EAN): 9781849969888 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts.Part I deals with the mathematical preliminaries: numerical linear algebra;
Автор: S?derstr?m Название: Errors-in-Variables Methods in System Identification ISBN: 3319750003 ISBN-13(EAN): 9783319750002 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification.
Описание: 1.Lossless Coding.- 2.Universal Coding on Finite Alphabets.- 3.Universal Coding on Infinite Alphabets.- 4.Model Order Estimation.- Notation.- Index.
Автор: Torsten S?derstr?m Название: Errors-in-Variables Methods in System Identification ISBN: 3030091252 ISBN-13(EAN): 9783030091255 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Нет в наличии.
Описание: This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.
Описание: The book is divided into four chapters, the first of which introduces readers to lossless coding, provides an intrinsic lower bound on the codeword length in terms of Shannon`s entropy, and presents some coding methods that can achieve this lower bound, provided the source distribution is known.
Описание: Most of the research and experiments in the fields of modeling and control systems have spent significant efforts to find rules from various complicated phenomena by principles, observations, measured data, logic derivations. The rules are normally summarized as concise and quantitative expressions or “models”. “Identification” provides mechanisms to establish the models and “control” provides mechanisms to improve system performances.This book reflects the relevant studies and applications in the area of renewable energies, with the latest research from interdisciplinary theoretical studies, computational algorithm development to exemplary applications. It discusses how modeling and control methods such as recurrent neural network, Pitch Angle Control, Fuzzy control, Sliding Mode Control and others are used in renewable systems. It covers topics as photovoltaic systems, wind turbines, maximum power point tracking, batteries for renewable energies, solar energy, thermal energy and so on. This book is edited and written by leading experts in the field and offers an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, control system and energy.
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