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Pachori / Tanveer

Machine Intelligence and Signal Analysis

Medium: Buch
ISBN: 978-981-13-0922-9
Verlag: Springer Nature Singapore
Erscheinungstermin: 08.08.2018
Lieferfrist: bis zu 10 Tage

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.


Produkteigenschaften


  • Artikelnummer: 9789811309229
  • Medium: Buch
  • ISBN: 978-981-13-0922-9
  • Verlag: Springer Nature Singapore
  • Erscheinungstermin: 08.08.2018
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2019
  • Serie: Advances in Intelligent Systems and Computing
  • Produktform: Kartoniert
  • Gewicht: 1171 g
  • Seiten: 767
  • Format (B x H x T): 155 x 235 x 42 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Chapter 1: Detecting R-peaks in Electrocardiogram signal using Hilbert envelope.- Chapter 2: Lung Nodule Identi?cation and Classi?cation from Distorted CT Images for Diagnosis andDetection of Lung Cancer.- Chapter 3: Baseline wander and power-line interferenceremoval 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 ?ltering 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.