Computational Intelligence and Neuroscience

Emerging Trends in Machine Learning for Signal Processing


Status
Published

1Eastern Macedonia and Thrace Institute of Technology, Kavala, Greece

2TEI of Thessaloniki, Sindos, Greece

3Seconda Università di Napoli (SUN), Aversa, Italy


Emerging Trends in Machine Learning for Signal Processing

Description

Recently, there is an increasing interest in developing “smart” devices and systems able to interact with their environment, for example, Internet of Things and Human-Machine Interfaces. The term “smart” is used to describe a set of advanced functionalities implemented utilizing sophisticated computational intelligence (CI) algorithms. Machine learning (ML) constitutes an important area of CI dealing with the ability of computers/machines to learn through knowledge representation, processing, and storing. ML offers solutions to difficult engineering problems, in a similar way to the humans’ brain processing. Moreover, considering the large amount and diversity of data (image, video, time series, 1-D signals, text, etc.) massively generated and stored by modern “smart” systems, the need for efficient ML algorithms in terms of accuracy and speed becomes increasingly important. In the light of this rapid development of machine learning tools, this special issue focuses on recent trends in applying ML methodologies for processing signals coming from any source. Τhis special issue aims to publish high-quality research papers as well as review articles addressing emerging trends in machine learning signal processing. Original contributions, not currently under review to a journal or a conference, are solicited in relevant areas.

Potential topics include but are not limited to the following:

  • Learning theory (supervised/unsupervised) for signal processing
  • Machine learning from big data
  • Deep learning for signal processing
  • Brain-computer interfacing
  • Cognitive systems for signal processing
  • Evolutionary computation for signal processing
  • Neural modeling and computation for signal processing
  • Hybrid intelligent systems
  • Intelligent agents
  • Neural hardware systems for signal processing
  • Learning, fusing classifiers
  • Kernel methods and high performance algorithms/implementations
  • Applications (audio/image/video/text processing in bioinformatics, communications, security, biomedicine, etc.)

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 6521367
  • - Editorial

Emerging Trends in Machine Learning for Signal Processing

George A. Papakostas | Konstantinos I. Diamantaras | Francesco A. N. Palmieri
  • Special Issue
  • - Volume 2017
  • - Article ID 9345969
  • - Research Article

Multimodal Personal Verification Using Likelihood Ratio for the Match Score Fusion

Long Binh Tran | Thai Hoang Le
  • Special Issue
  • - Volume 2017
  • - Article ID 5891417
  • - Research Article

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals

Eftychios Protopapadakis | Athanasios Voulodimos | ... | Matthaios Bimpas
  • Special Issue
  • - Volume 2017
  • - Article ID 5151895
  • - Research Article

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

Mohammad S. Islam | Khondaker A. Mamun | Hai Deng
  • Special Issue
  • - Volume 2017
  • - Article ID 4205141
  • - Research Article

Pathological Brain Detection Using Weiner Filtering, 2D-Discrete Wavelet Transform, Probabilistic PCA, and Random Subspace Ensemble Classifier

Debesh Jha | Ji-In Kim | ... | Goo-Rak Kwon
  • Special Issue
  • - Volume 2017
  • - Article ID 3105053
  • - Research Article

A Novel Active Semisupervised Convolutional Neural Network Algorithm for SAR Image Recognition

Fei Gao | Zhenyu Yue | ... | Huiyu Zhou
  • Special Issue
  • - Volume 2017
  • - Article ID 2157852
  • - Research Article

Application of the Intuitionistic Fuzzy InterCriteria Analysis Method with Triples to a Neural Network Preprocessing Procedure

Sotir Sotirov | Vassia Atanassova | ... | Jivko Tomov
  • Special Issue
  • - Volume 2017
  • - Article ID 5317850
  • - Research Article

Patch-Based Principal Component Analysis for Face Recognition

Tai-Xiang Jiang | Ting-Zhu Huang | ... | Tian-Hui Ma
Computational Intelligence and Neuroscience
 Journal metrics
Acceptance rate28%
Submission to final decision79 days
Acceptance to publication37 days
CiteScore4.700
Impact Factor2.284
 Submit

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.