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: Machine Intelligence and Signal Analysis
  name:
    name part: Tanveer, M.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Pachori, Ram Bilas.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XX, 767 p. 301 illus., 224 illus. in color. online resource.
  abstract: The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.
  table of contents: Chapter 1: Detecting R-peaks in Electrocardiogram signal using Hilbert envelope -- Chapter 2: Lung Nodule Identiﬁcation and Classiﬁcation from Distorted CT Images for Diagnosis and Detection of Lung Cancer -- Chapter 3: Baseline wander and power-line interference removal from ECG signals using Fourier decomposition method -- Chapter 4: Baseline wander and power-line interference removal from ECG signals using Fourier decomposition method -- Chapter 5: An Empirical Analysis of Instance-based Transfer Learning Approach on Protease Substrate Cleavage Sites Prediction -- Chapter 6: Comparison analysis: single and multichannel EMD based ﬁltering with application to BCI -- Chapter 7: A 2-norm Squared Fuzzy-based Least Squares Twin Parametric-margin Support Vector Machine -- Chapter 8: Redesign of a Railway Coach for Safe and Independent Travel of Elderly.
  note: edited by M. Tanveer, Ram Bilas Pachori.
  subject:
    topic: Computational intelligence
  subject:
    topic: Signal processing
  subject:
    topic: Image processing
  subject:
    topic: Speech processing systems
  subject:
    topic: Computer communication systems
  subject:
    topic: Power electronics
  subject:
    topic: Computational Intelligence
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Computer Communication Networks
  subject:
    topic: Power Electronics, Electrical Machines and Networks
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Advances in Intelligent Systems and Computing, 748
  identifier: 9789811309236
  identifier: https://doi.org/10.1007/978-981-13-0923-6
  record info:
    record creation date: 180807
    record change date: 20191021221448.0
    record identifier: 978-981-13-0923-6