Download or read book Biomimetic Spike based Algorithms and Hardware for Sound Classification Localization and Speech Recognition written by Yirong Pu and published by . This book was released on 2011 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: The objective of the thesis work is to design real-time, spike-based algorithms and implementation for biomimetic sound processing systems. An acoustic direction finding (ADF) system was designed and implemented in hardware to process transient sounds. Additionally, a top-down attentional mechanism model based on a study of mammalian brain activity was designed and explored to improve speech recognition. The front-end of the ADF system, which mimics a mammalian peripheral auditory system, generates spiking neuron firings as its output. The back-end algorithm was developed in MATLAB and an FPGA-based neural network was its final embodiment. The algorithm accomplishes sound detection, classification, direction finding, and localization of various kinds of audio data under noisy conditions and from reverberant environments. The attentional model was integrated with the front-end processing to help segregate a target sound source from masker sound sources as well as improving the classification accuracy of the target source. The neural-network-based sound classification and localization algorithm was first developed and tested using weaponry sound data obtained in the field. The algorithm is able to differentiate and trace various gunfire acoustic signatures in the presence of high background noise. The algorithm can locate the sound source by using single or multiple microphone array sites. Compared to a least square time difference of arrival algorithm, the neural-network-based algorithm has higher detection rate and more accurate localization. The complete back-end processing system was implemented on a single Xilinx Virtex-5 FPGA chip. The neural-network-based algorithm was also modified for a frog habitat monitoring application to demonstrate that the algorithm can be useful for applications other than weaponry classification and localization. Literature was reviewed and a functional, biologically-based, top-down attentional model was formulated, coded, and tested using speech signals with varying target masker ratios. The model improves the correctness of word identification of target speech by up to 50% in a noisy environment when the masker source is either a white noise signal or a speech- like signal. The thesis work presents the first spike-based transient sound classification and localization algorithm using neural networks, the first spike-based frog habitat monitoring algorithm, and a novel top-down, biologically-based attentional model.
Download or read book Neuroscience inspired Computational Systems for Speech Recognition Under Noisy Conditions written by Phillip Schafer and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Humans routinely recognize speech in challenging acoustic environments with background music, engine sounds, competing talkers, and other acoustic noise. However, today's automatic speech recognition (ASR) systems perform poorly in such environments. In this dissertation, I present novel methods for ASR designed to approach human-level performance by emulating the brain's processing of sounds. I exploit recent advances in auditory neuroscience to compute neuron-based representations of speech, and design novel methods for decoding these representations to produce word transcriptions. I begin by considering speech representations modeled on the spectrotemporal receptive fields of auditory neurons. These representations can be tuned to optimize a variety of objective functions, which characterize the response properties of a neural population. I propose an objective function that explicitly optimizes the noise invariance of the neural responses, and find that it gives improved performance on an ASR task in noise compared to other objectives. The method as a whole, however, fails to significantly close the performance gap with humans. I next consider speech representations that make use of spiking model neurons. The neurons in this method are feature detectors that selectively respond to spectrotemporal patterns within short time windows in speech. I consider a number of methods for training the response properties of the neurons. In particular, I present a method using linear support vector machines (SVMs) and show that this method produces spikes that are robust to additive noise. I compute the spectrotemporal receptive fields of the neurons for comparison with previous physiological results. To decode the spike-based speech representations, I propose two methods designed to work on isolated word recordings. The first method uses a classical ASR technique based on the hidden Markov model. The second method is a novel template-based recognition scheme that takes advantage of the neural representation's invariance in noise. The scheme centers on a speech similarity measure based on the longest common subsequence between spike sequences. The combined encoding and decoding scheme outperforms a benchmark system in extremely noisy acoustic conditions. Finally, I consider methods for decoding spike representations of continuous speech. To help guide the alignment of templates to words, I design a syllable detection scheme that robustly marks the locations of syllabic nuclei. The scheme combines SVM-based training with a peak selection algorithm designed to improve noise tolerance. By incorporating syllable information into the ASR system, I obtain strong recognition results in noisy conditions, although the performance in noiseless conditions is below the state of the art. The work presented here constitutes a novel approach to the problem of ASR that can be applied in the many challenging acoustic environments in which we use computer technologies today. The proposed spike-based processing methods can potentially be exploited in efficient hardware implementations and could significantly reduce the computational costs of ASR. The work also provides a framework for understanding the advantages of spike-based acoustic coding in the human brain.
Download or read book Binaural Hearing written by Ruth Y. Litovsky and published by Springer Nature. This book was released on 2021-03-01 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of Binaural Hearing involves studies of auditory perception, physiology, and modeling, including normal and abnormal aspects of the system. Binaural processes involved in both sound localization and speech unmasking have gained a broader interest and have received growing attention in the published literature. The field has undergone some significant changes. There is now a much richer understanding of the many aspects that comprising binaural processing, its role in development, and in success and limitations of hearing-aid and cochlear-implant users. The goal of this volume is to provide an up-to-date reference on the developments and novel ideas in the field of binaural hearing. The primary readership for the volume is expected to be academic specialists in the diverse fields that connect with psychoacoustics, neuroscience, engineering, psychology, audiology, and cochlear implants. This volume will serve as an important resource by way of introduction to the field, in particular for graduate students, postdoctoral scholars, the faculty who train them and clinicians.
Download or read book Event Based Neuromorphic Systems written by Shih-Chii Liu and published by John Wiley & Sons. This book was released on 2015-02-16 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities. This cross-disciplinary text establishes how circuit building blocks are combined in architectures to construct complete systems. These include vision and auditory sensors as well as neuronal processing and learning circuits that implement models of nervous systems. Techniques for building multi-chip scalable systems are considered throughout the book, including methods for dealing with transistor mismatch, extensive discussions of communication and interfacing, and making systems that operate in the real world. The book also provides historical context that helps relate the architectures and circuits to each other and that guides readers to the extensive literature. Chapters are written by founding experts and have been extensively edited for overall coherence. This pioneering text is an indispensable resource for practicing neuromorphic electronic engineers, advanced electrical engineering and computer science students and researchers interested in neuromorphic systems. Key features: Summarises the latest design approaches, applications, and future challenges in the field of neuromorphic engineering. Presents examples of practical applications of neuromorphic design principles. Covers address-event communication, retinas, cochleas, locomotion, learning theory, neurons, synapses, floating gate circuits, hardware and software infrastructure, algorithms, and future challenges.
Download or read book Brain Computer Interface Research written by Christoph Guger and published by Springer. This book was released on 2017-04-29 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the prize-winning brain-computer-interface (BCI) projects honored in the community's most prestigious annual award. BCIs enable people to communicate and control their limbs and/or environment using thought processes alone. Research in this field continues to develop and expand rapidly, with many new ideas, research groups, and improved technologies having emerged in recent years. The chapters in this volume feature the newest developments from many of the best labs worldwide. They present both non-invasive systems (based on the EEG) and intracortical methods (based on spikes or ECoG), and numerous innovative applications that will benefit new user groups
Download or read book Neural Engineering written by Chris Eliasmith and published by MIT Press. This book was released on 2003 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.
Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Download or read book Analog VLSI written by Shih-Chii Liu and published by MIT Press. This book was released on 2002 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the design of analog VLSI circuits. Neuromorphic engineers work to improve the performance of artificial systems through the development of chips and systems that process information collectively using primarily analog circuits. This book presents the central concepts required for the creative and successful design of analog VLSI circuits. The discussion is weighted toward novel circuits that emulate natural signal processing. Unlike most circuits in commercial or industrial applications, these circuits operate mainly in the subthreshold or weak inversion region. Moreover, their functionality is not limited to linear operations, but also encompasses many interesting nonlinear operations similar to those occurring in natural systems. Topics include device physics, linear and nonlinear circuit forms, translinear circuits, photodetectors, floating-gate devices, noise analysis, and process technology.
Download or read book Genetic Algorithms in Search Optimization and Machine Learning written by David Edward Goldberg and published by Addison-Wesley Professional. This book was released on 1989 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applications of genetic algorithms. Advanced operators and techniques in genetic search. Introduction to genetics-based machine learning. Applications of genetics-based machine learning. A look back, a glance ahead. A review of combinatorics and elementary probability. Pascal with random number generation for fortran, basic, and cobol programmers. A simple genetic algorithm (SGA) in pascal. A simple classifier system(SCS) in pascal. Partition coefficient transforms for problem-coding analysis.
Download or read book Neural Engineering written by Bin He and published by Springer Science & Business Media. This book was released on 2013-01-09 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Engineering, 2nd Edition, contains reviews and discussions of contemporary and relevant topics by leading investigators in the field. It is intended to serve as a textbook at the graduate and advanced undergraduate level in a bioengineering curriculum. This principles and applications approach to neural engineering is essential reading for all academics, biomedical engineers, neuroscientists, neurophysiologists, and industry professionals wishing to take advantage of the latest and greatest in this emerging field.
Download or read book Efficient Learning Machines written by Mariette Awad and published by Apress. This book was released on 2015-04-27 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning.
Download or read book Introduction to Autonomous Mobile Robots second edition written by Roland Siegwart and published by MIT Press. This book was released on 2011-02-18 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive introduction to all aspects of mobile robotics, from algorithms to mechanisms. Mobile robots range from the Mars Pathfinder mission's teleoperated Sojourner to the cleaning robots in the Paris Metro. This text offers students and other interested readers an introduction to the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers the field comprises. The text focuses on mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks, including locomotion, sensing, localization, and motion planning. It synthesizes material from such fields as kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence, and probability theory. The book presents the techniques and technology that enable mobility in a series of interacting modules. Each chapter treats a different aspect of mobility, as the book moves from low-level to high-level details. It covers all aspects of mobile robotics, including software and hardware design considerations, related technologies, and algorithmic techniques. This second edition has been revised and updated throughout, with 130 pages of new material on such topics as locomotion, perception, localization, and planning and navigation. Problem sets have been added at the end of each chapter. Bringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook or a working tool for beginning practitioners. Curriculum developed by Dr. Robert King, Colorado School of Mines, and Dr. James Conrad, University of North Carolina-Charlotte, to accompany the National Instruments LabVIEW Robotics Starter Kit, are available. Included are 13 (6 by Dr. King and 7 by Dr. Conrad) laboratory exercises for using the LabVIEW Robotics Starter Kit to teach mobile robotics concepts.
Download or read book Pulsed Neural Networks written by Wolfgang Maass and published by MIT Press. This book was released on 2001-01-26 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most practical applications of artificial neural networks are based on a computational model involving the propagation of continuous variables from one processing unit to the next. In recent years, data from neurobiological experiments have made it increasingly clear that biological neural networks, which communicate through pulses, use the timing of the pulses to transmit information and perform computation. This realization has stimulated significant research on pulsed neural networks, including theoretical analyses and model development, neurobiological modeling, and hardware implementation. This book presents the complete spectrum of current research in pulsed neural networks and includes the most important work from many of the key scientists in the field. Terrence J. Sejnowski's foreword, "Neural Pulse Coding," presents an overview of the topic. The first half of the book consists of longer tutorial articles spanning neurobiology, theory, algorithms, and hardware. The second half contains a larger number of shorter research chapters that present more advanced concepts. The contributors use consistent notation and terminology throughout the book. Contributors Peter S. Burge, Stephen R. Deiss, Rodney J. Douglas, John G. Elias, Wulfram Gerstner, Alister Hamilton, David Horn, Axel Jahnke, Richard Kempter, Wolfgang Maass, Alessandro Mortara, Alan F. Murray, David P. M. Northmore, Irit Opher, Kostas A. Papathanasiou, Michael Recce, Barry J. P. Rising, Ulrich Roth, Tim Schönauer, Terrence J. Sejnowski, John Shawe-Taylor, Max R. van Daalen, J. Leo van Hemmen, Philippe Venier, Hermann Wagner, Adrian M. Whatley, Anthony M. Zador
Download or read book Brain Computer Interfaces written by Jonathan Wolpaw and published by Oxford University Press. This book was released on 2012-01-24 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: A recognizable surge in the field of Brain Computer Interface (BCI) research and development has emerged in the past two decades. This book is intended to provide an introduction to and summary of essentially all major aspects of BCI research and development. Its goal is to be a comprehensive, balanced, and coordinated presentation of the field's key principles, current practice, and future prospects.
Download or read book Tactical Biopolitics written by Beatriz Da Costa and published by MIT Press. This book was released on 2010-08-13 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientists, scholars, and artists consider the political significance of recent advances in the biological sciences. Popular culture in this “biological century” seems to feed on proliferating fears, anxieties, and hopes around the life sciences at a time when such basic concepts as scientific truth, race and gender identity, and the human itself are destabilized in the public eye. Tactical Biopolitics suggests that the political challenges at the intersection of life, science, and art are best addressed through a combination of artistic intervention, critical theorizing, and reflective practices. Transcending disciplinary boundaries, contributions to this volume focus on the political significance of recent advances in the biological sciences and explore the possibility of public participation in scientific discourse, drawing on research and practice in art, biology, critical theory, anthropology, and cultural studies. After framing the subject in terms of both biology and art, Tactical Biopolitics discusses such topics as race and genetics (with contributions from leading biologists Richard Lewontin and Richard Levins); feminist bioscience; the politics of scientific expertise; bioart and the public sphere (with an essay by artist Claire Pentecost); activism and public health (with an essay by Treatment Action Group co-founder Mark Harrington); biosecurity after 9/11 (with essays by artists' collective Critical Art Ensemble and anthropologist Paul Rabinow); and human-animal interaction (with a framing essay by cultural theorist Donna Haraway). Contributors Gaymon Bennett, Larry Carbone, Karen Cardozo, Gary Cass, Beatriz da Costa, Oron Catts, Gabriella Coleman, Critical Art Ensemble, Gwen D'Arcangelis, Troy Duster, Donna Haraway, Mark Harrington, Jens Hauser, Kathy High, Fatimah Jackson, Gwyneth Jones, Jonathan King, Richard Levins, Richard Lewontin, Rachel Mayeri, Sherie McDonald, Claire Pentecost, Kavita Philip, Paul Rabinow, Banu Subramanian, subRosa, Abha Sur, Samir Sur, Jacqueline Stevens, Eugene Thacker, Paul Vanouse, Ionat Zurr
Download or read book Auditory Interfaces written by Stefania Serafin and published by Focal Press. This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Auditory Interfaces explores how human-computer interactions can be significantly enhanced through the improved use of the audio channel. Providing historical, theoretical and practical perspectives, the book begins with an introductory overview, before presenting cutting-edge research with chapters on embodied music recognition, nonspeech audio, and user interfaces. This book will be of interest to advanced students, researchers and professionals working in a range of fields, from audio sound systems, to human-computer interaction and computer science"--
Download or read book Humanoid Robotics A Reference written by Prahlad Vadakkepat and published by Springer. This book was released on 2017-02-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Humanoid Robotics provides a comprehensive compilation of developments in the conceptualization, design and development of humanoid robots and related technologies. Human beings have built the environment they occupy (living spaces, instruments and vehicles) to suit two-legged systems. Building systems, especially in robotics, that are compatible with the well-established, human-based surroundings and which could naturally interact with humans is an ultimate goal for all researches and engineers. Humanoid Robots are systems (i.e. robots) which mimic human behavior. Humanoids provide a platform to study the construction of systems that behave and interact like humans. A broad range of applications ranging from daily housework to complex medical surgery, deep ocean exploration, and other potentially dangerous tasks are possible using humanoids. In addition, the study of humanoid robotics provides a platform to understand the mechanisms and offers a physical visual of how humans interact, think, and react with the surroundings and how such behaviors could be reassembled and reconstructed. Currently, the most challenging issue with bipedal humanoids is to make them balance on two legs, The purportedly simple act of finding the best balance that enables easy walking, jumping and running requires some of the most sophisticated development of robotic systems- those that will ultimately mimic fully the diversity and dexterity of human beings. Other typical human-like interactions such as complex thought and conversations on the other hand, also pose barriers for the development of humanoids because we are yet to understand fully the way in which we humans interact with our environment and consequently to replicate this in humanoids.
