rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Statistical signal processing for neuroscience and neurotechnology
  name:
    name part: Oweiss, Karim G.
  name:
    name part: ScienceDirect (Online service)
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: mau
    place:
      place term: Burlington, MA
    publisher: Academic Press/Elsevier
    date issued: ©2010
    date issued: 2010
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xxii, 411 pages) : illustrations
  abstract: This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents new theory, algorithms, software and hardware tools that are specifically tailored to the nature of the neurobiological environment. It gives a broad overview of the basic principles, theories and methods in statistical signal processing for basic and applied neuroscience problems. Written by experts in the field, the book is an ideal reference for researchers working in the field of neural engineering, neural interface, computational neuroscience, neuroinformatics, neuropsychology and neural physiology. By giving a broad overview of the basic principles, theories and methods, it is also an ideal introduction to statistical signal processing in neuroscience. A comprehensive overview of the specific problems in neuroscience that require application of existing and development of new theory, techniques, and technology by the signal processing community Contains state-of-the-art signal processing, information theory, and machine learning algorithms and techniques for neuroscience research Presents quantitative and information-driven science that has been, or can be, applied to basic and translational neuroscience problems.
  table of contents: Detection and classification of extracellular action potential recordings / Karim G. Oweiss and Mehdi A. Aghagolzadeh -- Information-theoretic analysis of neural data / Don H. Johnson -- Identification of nonlinear dynamics in neural population activity / Dong Song and Theodore W. Berger -- Graphical models of functional and effective neuronal connectivity / Seif M. Eldawlatly and Karim G. Oweiss -- State-space modeling of neural spike train and behavioral data / Zhe Chen, Riccardo Barbieri, and Emery N. Brown -- Neural decoding for motor and communication prostheses / Byron M. Yu [and others] -- Inner products for representation and learning in the spike train domain / Antonio R.C. Paiva, Il Park, and José C. Príncipe -- Signal processing and machine learning for single-trial analysis of simultaneously acquired EEG and fMRI / Paul Sajda [and others] -- Statistical pattern recognition and machine learning in brain-computer interfaces / Rajesh P.N. Rao and Reinhold Scherer -- Prediction of muscle activity from cortical signals to restore hand grasp in subjects with spinal cord injury / Emily R. Oby [and others].
  note: edited by Karim G. Oweiss.
  note: Includes bibliographical references and index.
  subject:
    topic: Electroencephalography
  subject:
    topic: Signal processing
    topic: Digital techniques
  subject:
    topic: Brain mapping
  subject:
    topic: Human-machine systems
  subject:
    topic: Brain
    topic: physiology
  subject:
    topic: Signal Processing, Computer-Assisted
  subject:
    topic: Brain Mapping
    topic: instrumentation
  subject:
    topic: Man-Machine Systems
  subject:
    topic: Prostheses and Implants
  subject:
    topic: User-Computer Interface
  subject:
    topic: Electroencephalography
  subject:
    topic: Brain Mapping
  subject:
    topic: Électroencéphalographie
  subject:
    topic: Traitement du signal
    topic: Techniques numériques
  subject:
    topic: Cartographie cérébrale
  subject:
    topic: Systèmes homme-machine
  subject:
    topic: HEALTH & FITNESS
    topic: Diseases
    topic: Nervous System (incl. Brain)
  subject:
    topic: MEDICAL
    topic: Neurology
  subject:
    topic: Human-machine systems
  subject:
    topic: Brain mapping
  subject:
    topic: Electroencephalography
  subject:
    topic: Signal processing
    topic: Digital techniques
  classification: QP376.5 .S73 2010
  classification: 616.8/047547
  classification: 2010 J-202
  classification: WL 26.5 S7976 2010
  related item:
    title info:
      title: Statistical signal processing for neuroscience and neurotechnology
    origin info:
      publisher: Burlington, MA : Academic Press/Elsevier, ©2010
    identifier: (DLC) 2010012521
    identifier: (OCoLC)607465442
  identifier: 0080962963
  identifier: 9780080962962
  identifier: 9780123750273
  identifier: 012375027X
  identifier: 2010012521
  identifier: 177376:173809 Elsevier Science & Technology
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: OPELS
    record creation date: 101005
    record change date: 20260326183824.2
    record identifier: in00005746067
    language of cataloging:
      language term: eng