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Nonlinear Speech Modeling and Applications : Advanced Lectures and Revised Selected Papers
Presents the revised tutorial lectures given at the International Summer School on Nonlinear Speech Processing-Algorithms and Analysis held in Vietri sul Mare, Salerno, Italy in September 2004. The 14 revised tutorial lectures by leading international researchers are organized in topical sections on dealing with nonlinearities in speech signals, acoustic-to-articulatory modeling of speech phenomena, data driven and speech processing algorithms, and algorithms and models based on speech perception mechanisms. Besides the tutorial lectures, 15 revised reviewed papers are included presenting original research results on task oriented speech applications.
Nonlinear Analyses and Algorithms for Speech Processing ; International Conference on Non-Linear Speech Processing, NOLISP 2005, Barcelona, Spain, April 19-22, 2005, Revised Selected Papers
We present in this volume the collection of ?nally accepted papers of NOLISP 2005 conference. It has been the third event in a series of events related to N- linear speech processing, in the framework of the European COST action 277 “Nonlinear speech processing”. Many speci?cs of the speech signal are not well addressed by conv- tional models currently used in the ?eld of speech processing. The purpose of NOLISP is to present and discuss novel ideas, work and results related to alternative techniques for speech processing, which depart from mainstream approaches. With this intention in mind, we provide an open forum for discussion. Alt- nate approaches are appreciated, although the results achieved at present may not clearly surpass results based on state-of-the-art methods. The call for papers was launched at the beginning of 2005, addressing the following domains: 1. Non-Linear Approximation and Estimation 2. Non-Linear Oscillators and Predictors 3. Higher-Order Statistics 4. Independent Component Analysis 5. Nearest Neighbors 6. Neural Networks 7. Decision Trees 8. Non-Parametric Models 9. Dynamics of Non-Linear Systems 10. Fractal Methods 11. Chaos Modeling 12. Non-Linear Di?erential Equations 13. Others All the main ?elds of speech processing are targeted by the workshop, namely: 1. Speech Coding:Thebit rateavailablefor speechsignalsmustbe strictly l- ited in order to accommodate the constraints of the channel resource.
Modeling Communication with Robots and Virtual Humans ; Second ZiF Research Group International Workshop on Embodied Communication in Humans and Machines, Bielefeld, Germany, April 5-8, 2006, Revised Selected Papers
The 17 articles in this state-of-the-art survey address artificial intelligence research on communicative agents and also provide an interdisciplinary perspective from linguistics, behavioral research, theoretical biology, philosophy, communication psychology, and computational neuroscience. The topics include studies on human multimodal communication; the modeling of feedback signals, facial expression, eye contact, and deception; the recognition and comprehension of hand gestures and head movements; communication interfaces for humanoid robots; the evolution of cognition and language; emotion and social appraisal in nonverbal communication; dialogue models and methodologies; theory of mind and intentionality; complex systems, dynamic field theory, and connectionist modeling.
Mind conversation = التنبؤ بالحروف العربية من خلال الإشارات الدماغية
Throughout history, humans have long dreamed of understanding what goes on inside the human mind—what people are thinking or feeling. It seemed like something from a far-off future or a magical realm. But now, thanks to amazing technology called EEG and BCI, this dream is turning into reality. EEG stands for electroencephalography. It's a way of listening to what the brain is up to by placing small sensors on or near the head. These sensors pick up tiny electrical signals produced by the brain's activity. It's like eavesdropping on the brain's conversations with itself. BCI, or Brain-Computer Interface, is like a bridge between the brain and machines. It lets the brain talk to devices or computers. This means people can control things without using their hands or voices. Our system takes advantage of EEG and BCI to create something helpful, a special mobile app. This app is designed for people who can't move their bodies, like those who are paralyzed. It helps them use their phones to express what they are thinking about.
Microelectronic Circuits
Devices and basic circuits -- Signals, amplifiers and semiconductors -- Operational amplifiers -- Diodes -- Bipolar junction transistors (BJTS) -- Mos field-effect transistors (MOSFETS) -- Transistor amplifiers -- Analog integrated circuits -- Building blocks of integrated-circuit amplifiers -- Differential and multistage amplifiers -- Frequency response -- Feedback -- Output stages and power amplifiers -- Operational-amplifier circuits -- Filters and oscillators -- Digital integrated circuits -- CMOS digital logic circuits -- Digital Design: Power, Speed, and Area -- Memory and Clocking Circuits
Medical data processing and analysis
Medical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient’s status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results—from carrying out measurements to experiments and observations.
Instrumaster
Experiments with different neural network structures and algorithms in order to achieve musical note recognition as well as musical instrument recognition, all bundled in a mobile application. It also aims to create the most effective music-learning application that works completely offline, which is hard to find in modern music applications. The paper also explores why the instrument identifying AI is solely based on Multi-Layer Perceptron (MLP) and why the note-identifying AI system was chosen to be a ML system over CNN or other deep-learning trained AI. The paper presents feature extraction methods for audio signals and files and dives deep into the process, such as FFT, MFCCs, Wavelengths, sampling rates, etc. It also touches on Logistic Regression Algorithms, their limitations, and their performance with the different use cases in the application. All these techniques are then compared side by side for maximally added value, making this research paper a good reference for any future developers looking to find optimal neural networks techniques when it comes to audio processing and analysis.
Independent component analysis and signal separation ; 7th International Conference, ICA 2007, London, UK, September 9-12, 2007, Proceedings
Independent Component Analysis and Signal Separation has applications at the intersection of many science and engineering disciplinesconcernedwithunderstandingandextractingusefulinformationfrom data as diverse as neuronal activity and brain images, bioinformatics, com- nications, the World Wide Web, audio, video, sensor signals, or time series.
Generator remote controlling using internet connection
The traditional technique of monitoring the electricity generated through regular checks on the alternator variables: oil, temperature, voltage and current on a daily basis. Therefore, maintaining a normal performance cycle requires hard work and is often imprecise. The idea is to create an application that monitors wireless generators using the popular smartphone Android operating system. Implemented sensors deliver analog signals that provide real-time data on the status of the generator. This data is converted and programmed through the Node MCU microcontroller, which reads the results from the sensors and then converts into a signal, which is transmitted to the android phone, through a router. Thus live feedback of the generator status is ensured. In addition, this project provides a control button that can actually turn this generator on and off. This project is the first step towards bringing systems and control together as it revolutionizes the ideology of monitoring and displaying real-time data that can be implemented in different fields according to different needs. These fields include electricity, mechanics, and communications.
Electronic Noise and Interfering Signals
Electronic Noise and Interfering Signals" is a comprehensive reference book on noise and interference in electronic circuits, with particular focus on low-noise design. The first part of the book deals with mechanisms, modeling, and computation of intrinsic noise which is generated in every electronic device. The second part analyzes the coupling mechanisms which can lead to a contamination of circuits by parasitic signals and provides appropriate solutions to this problem. The last part contains more than 100 practical, elaborate case studies
Electronic engineering for neuromedicine
Advances in electronics have revolutionized diagnostic tools and created mobile medicine, touch-sensitive prosthetics, remote surgery, and artificial organs such as hearts, retinas, and bionic skins. This reference text shows the number of ways in which electronic engineering feeds into neuromedicine namely: the modelling and simulation of the brain, providing access to the brain, analysis of the signals and activities of the brain and influencing the function of the brain for therapeutic purposes. The areas of electronic engineering considered are electronic circuits, spectral analysis, filtering of signals, electromagnetic fields and wave propagation. The book is a valuable source to medical students and practitioners as well as electronic engineering and physics students and graduates.
EEG signal processing for biomedical applications
Focuses on electroencephalography (EEG) signal processing in biomedical engineering applications. EEG signals are used widely in clinical and research settings to provide cognitive and emotional state information. In addition to capturing complex neural patterns at high speeds, EEG signals are a reliable and non-invasive way of measuring the electrical activity in the brain. By examining various novel analysis and signal processing methods, this collection of papers provides a better understanding of cognitive states and brain activity.
Deep structure, singularities, and computer vision ; 1st international workshop, DSSCV 2005, Maastricht, The Netherlands, June 9-10, 2005, revised selected papers
Constitutes the refereed post-proceedings of the First International Workshop on Deep Structure, Singularities, and Computer Vision, DSSCV 2005, held in Maastricht. This book represents in understanding the relation between structural, topological information represented by singularities and metric information of signals, shapes, and colors.
Deep Learning to See : Towards New Foundations of Computer Vision
Topics and features: Presents a curiosity-driven approach, posing questions to stimulate readers to design novel computational models of vision Offers a rethinking of computer vision, arguing for an approach based on vision in nature, versus regarding visual signals as collections of images Provides an interdisciplinary commentary, aiming to unify computer vision, machine learning, human vision, and computational neuroscience Serving to inspire and stimulate critical reflection and discussion, yet requiring no prior advanced technical knowledge, the text can naturally be paired with classic textbooks on computer vision to better frame the current state of the art, open problems, and novel potential solutions.
Control problems for conservation laws with traffic applications: modeling, analysis, and numerical methods
Conservation and balance laws on networks have been the subject of much research interest given their wide range of applications to real-world processes, particularly traffic flow. This open access monograph is the first to investigate different types of control problems for conservation laws that arise in the modeling of vehicular traffic. Four types of control problems are discussed - boundary, decentralized, distributed, and Lagrangian control - corresponding to, respectively, entrance points and tolls, traffic signals at junctions, variable speed limits, and the use of autonomy and communication. Because conservation laws are strictly connected to Hamilton-Jacobi equations, control of the latter is also considered.
Computer Music Modeling and Retrieval. Sense of Sounds ; 4th International Symposium, CMMR 2007, Copenhagen, Denmark, August 27-31, 2007. Revised Papers
This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Computer Music Modeling and Retrieval Symposium, CMMR 2007, held in Copenhagen, Denmark, in August 2007 jointly with the International Computer Music Conference 2007, ICMC 2007.
Code : The Hidden Language of Computer Hardware and Software ; 2nd ed
The classic guide to how computers work, updated with new chapters and interactive graphics Computers are everywhere --- most obviously in our laptops and smartphones, but also our cars, televisions, microwave ovens, alarm clocks, robot vacuum cleaners, and other smart appliances. Have you ever wondered what goes on inside these devices to make our lives easier but occasionally more infuriating? Explores more deeply the bit-by-bit, gate-by-gate construction of the heart of every smart device ― the central processing unit that combines the simplest of basic operations to perform the most complex of feats. Along with new chapters, Petzold created a new website, CodeHiddenLanguage.com, that uses animated interactive graphics to make computers even easier to comprehend.
Machine learning for biomedical application
Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.
Brain thoughts recognition
Humans controlling machines with their minds may sound like something from a scifi movie, but it’s becoming a reality through brain-computer interfaces BCI. Where BCI technology allows a human brain and an external device to talk to each other—to exchange signals. It gives humans the ability to directly control machines, without the physical constraints of the body. There are two ways to implement the BCI: Noninvasive tools often use sensors applied on or near the head to track and record brain activity, or Invasive BCI would require surgery. Electronic devices would need to be implanted beneath the skull, directly into the brain, to target specific sets of neurons. In order to implement a non-invasive BCI in a mobile phone, this study developed a mobile application to help paralyzed people who do not have the ability to use their phones to spend their basic daily needs, such as using the keyboard and interacting with PDF, etc.
Bioelectricity : A Quantitative Approach
"The authors’ goal in producing this book was to provide an introductory text to electrophysiology, based on a quantitative approach. In attempting to achieve this goal, therefore, the authors have opened the book with a useful, and digestible, introduction to various aspects of the mathematics relevant to this field, including vectors, introduction to Laplace, Gauss’s theorem, and Green’s theorem. This book will be useful for students in medical physics and biomedical engineering wishing to enter the field of electrophysiological investigation. It will also be helpful for biologists and physiologists who wish to understand the mathematical treatment of the processes and signals at the center of the interesting interdisciplinary field.
