Neuronal Ensemble Modeling and Analysis with Variable Order Markov Models PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Neuronal Ensemble Modeling and Analysis with Variable Order Markov Models PDF full book. Access full book title Neuronal Ensemble Modeling and Analysis with Variable Order Markov Models by Antonio Giuliano Zippo. Download full books in PDF and EPUB format.
Author: Antonio Giuliano Zippo
Publisher: Ledizioni
ISBN: 8895994574
Category : Mathematics
Languages : en
Pages : 157
Get Book Here
Book Description
Neuronal cells (neurons) mainly transmit signals by action potentials or spikes.Neuronal electrical activity is recorded from experimental animals bymicroelectrodesplaced in specific brain areas. These electrochemical fast phenomenaoccur as all-or-none events and can be analyzed as boolean sequences. Followingthis approach, several computational analyses reported most variable neuronalbehaviors expressed through a large variety of firing patterns [13]. Thesepatternshave been modeled as symbolic strings with a number of different techniques[23, 55]The results obtained with these methods come (i) from Ventrobasal ThalamicNuclei (VB) and Somatosensory Cortex (SSI) in Chronic Pain Animals (CPAs), (ii) from Primary Visual (V1) and (SSI) in rat Cortices and, finally, (iii) fromIL human Thalamus Nuclei in patients suffering from states of disorderedconsciousnesslike Persistent Vegetative State (PVS) and Minimum Conscious State(MCS).
Author: Antonio Giuliano Zippo
Publisher: Ledizioni
ISBN: 8895994574
Category : Mathematics
Languages : en
Pages : 157
Get Book Here
Book Description
Neuronal cells (neurons) mainly transmit signals by action potentials or spikes.Neuronal electrical activity is recorded from experimental animals bymicroelectrodesplaced in specific brain areas. These electrochemical fast phenomenaoccur as all-or-none events and can be analyzed as boolean sequences. Followingthis approach, several computational analyses reported most variable neuronalbehaviors expressed through a large variety of firing patterns [13]. Thesepatternshave been modeled as symbolic strings with a number of different techniques[23, 55]The results obtained with these methods come (i) from Ventrobasal ThalamicNuclei (VB) and Somatosensory Cortex (SSI) in Chronic Pain Animals (CPAs), (ii) from Primary Visual (V1) and (SSI) in rat Cortices and, finally, (iii) fromIL human Thalamus Nuclei in patients suffering from states of disorderedconsciousnesslike Persistent Vegetative State (PVS) and Minimum Conscious State(MCS).
Author: Stefano Zampini
Publisher: Ledizioni
ISBN: 8895994663
Category : Mathematics
Languages : en
Pages : 269
Get Book Here
Book Description
Recent advances in biotechnology and the availability of ever more powerful computers have led to the formulation of increasingly complex models at all levels of life sciences, in particular of cardiac electrophysiology. Multiscale modeling of the bioelectric activity of the heart, taking into account macroscopic (fiber architecture and anisotropy) and microscopic (cellular) features of the tissue, aim to develop predictive tools for future drug design and patient-specific therapies, using detailed and efficient three-dimensional solvers for the governing equations of tissue electrophysiology.
Author: Matteo Bianchi
Publisher: Ledizioni
ISBN: 8895994566
Category : Mathematics
Languages : en
Pages : 169
Get Book Here
Book Description
The scientific area this thesis belongs to is many-valued logics: this meanslogics in which, from the semantical point of view, we have "intermediate"truth-values, between 0 and 1 (which in turns are designated to represent, respectively, the "false" and the "true").The classical logic (propositional, for simplicity) is based on the fact thatevery statement is true or false: this is reflected by the excluded middle law, that is a theorem of this logic. However, there are many reasons that suggestto reject this law: for example, intuitionistic logic does not satisfy it, sincethis logic reflects a "constructive" conception of mathematics (see [Hey71, Tro69]).
Author: Paola M. V. Rancoita
Publisher: Ledizioni
ISBN: 8895994582
Category : Mathematics
Languages : en
Pages : 301
Get Book Here
Book Description
In this thesis, I study three stochastic methods that can be applied for the analysis of data in cancer research and, in particular, to cancer genomic data and to images of angiogenic processes. Cancer is a multistep process where the accumulation of genomic lesions alters cell biology. The latter is under control of several pathways and thus, cancer can arise via different mechanisms affecting different pathways. Due to the general complexity of this disease and the different types of tumors, the efforts of cancer research cover several research areas such as, for example, immunology, genetics, cell biology, angiogenesis.
Author: Marco Maggis
Publisher: Ledizioni
ISBN: 8895994590
Category : Mathematics
Languages : en
Pages : 143
Get Book Here
Book Description
Author: Iain L. MacDonald
Publisher: CRC Press
ISBN: 9780412558504
Category : Mathematics
Languages : en
Pages : 256
Get Book Here
Book Description
Discrete-valued time series are common in practice, but methods for their analysis are not well-known. In recent years, methods have been developed which are specifically designed for the analysis of discrete-valued time series. Hidden Markov and Other Models for Discrete-Valued Time Series introduces a new, versatile, and computationally tractable class of models, the "hidden Markov" models. It presents a detailed account of these models, then applies them to data from a wide range of diverse subject areas, including medicine, climatology, and geophysics. This book will be invaluable to researchers and postgraduate and senior undergraduate students in statistics. Researchers and applied statisticians who analyze time series data in medicine, animal behavior, hydrology, and sociology will also find this information useful.
Author: Walter Zucchini
Publisher: CRC Press
ISBN: 1315355205
Category : Mathematics
Languages : en
Pages : 272
Get Book Here
Book Description
Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data
Author: Zhe Chen
Publisher: Springer
ISBN: 3319719769
Category : Technology & Engineering
Languages : en
Pages : 337
Get Book Here
Book Description
This book shows how to develop efficient quantitative methods to characterize neural data and extra information that reveals underlying dynamics and neurophysiological mechanisms. Written by active experts in the field, it contains an exchange of innovative ideas among researchers at both computational and experimental ends, as well as those at the interface. Authors discuss research challenges and new directions in emerging areas with two goals in mind: to collect recent advances in statistics, signal processing, modeling, and control methods in neuroscience; and to welcome and foster innovative or cross-disciplinary ideas along this line of research and discuss important research issues in neural data analysis. Making use of both tutorial and review materials, this book is written for neural, electrical, and biomedical engineers; computational neuroscientists; statisticians; computer scientists; and clinical engineers.
Author: Wai-Ki Ching
Publisher: Springer Science & Business Media
ISBN: 1461463122
Category : Business & Economics
Languages : en
Pages : 259
Get Book Here
Book Description
This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end-of-chapter exercises, a new focus on management science, new applications of the models, and new examples with applications in financial risk management and modeling of financial data. This book consists of eight chapters. Chapter 1 gives a brief introduction to the classical theory on both discrete and continuous time Markov chains. The relationship between Markov chains of finite states and matrix theory will also be highlighted. Some classical iterative methods for solving linear systems will be introduced for finding the stationary distribution of a Markov chain. The chapter then covers the basic theories and algorithms for hidden Markov models (HMMs) and Markov decision processes (MDPs). Chapter 2 discusses the applications of continuous time Markov chains to model queueing systems and discrete time Markov chain for computing the PageRank, the ranking of websites on the Internet. Chapter 3 studies Markovian models for manufacturing and re-manufacturing systems and presents closed form solutions and fast numerical algorithms for solving the captured systems. In Chapter 4, the authors present a simple hidden Markov model (HMM) with fast numerical algorithms for estimating the model parameters. An application of the HMM for customer classification is also presented. Chapter 5 discusses Markov decision processes for customer lifetime values. Customer Lifetime Values (CLV) is an important concept and quantity in marketing management. The authors present an approach based on Markov decision processes for the calculation of CLV using real data. Chapter 6 considers higher-order Markov chain models, particularly a class of parsimonious higher-order Markov chain models. Efficient estimation methods for model parameters based on linear programming are presented. Contemporary research results on applications to demand predictions, inventory control and financial risk measurement are also presented. In Chapter 7, a class of parsimonious multivariate Markov models is introduced. Again, efficient estimation methods based on linear programming are presented. Applications to demand predictions, inventory control policy and modeling credit ratings data are discussed. Finally, Chapter 8 re-visits hidden Markov models, and the authors present a new class of hidden Markov models with efficient algorithms for estimating the model parameters. Applications to modeling interest rates, credit ratings and default data are discussed. This book is aimed at senior undergraduate students, postgraduate students, professionals, practitioners, and researchers in applied mathematics, computational science, operational research, management science and finance, who are interested in the formulation and computation of queueing networks, Markov chain models and related topics. Readers are expected to have some basic knowledge of probability theory, Markov processes and matrix theory.
Author: Longbing Cao
Publisher: Springer Nature
ISBN: 9819999154
Category :
Languages : en
Pages : 409
Get Book Here
Book Description
