IET Signal Processing

Aims & Scope

IET Signal Processing publishes research on a diverse range of signal processing and machine learning topics, covering a variety of applications, disciplines, modalities, and techniques in detection, estimation, inference, and classification problems.

The research published includes advances in algorithm design for the analysis of single and high-multi-dimensional data, sparsity, linear and non-linear systems, recursive and non-recursive digital filters and multi-rate filter banks, as well a range of topics that span from sensor array processing, deep convolutional neural network based approaches to the application of chaos theory, and far more.

Topics covered by scope include, but are not limited to: -advances in single and multi-dimensional filter design and implementation -linear and nonlinear, fixed and adaptive digital filters and multirate filter banks -statistical signal processing techniques and analysis -classical, parametric and higher order spectral analysis -signal transformation and compression techniques, including time-frequency analysis -system modelling and adaptive identification techniques -machine learning based approaches to signal processing -Bayesian methods for signal processing, including Monte-Carlo Markov-chain and particle filtering techniques -theory and application of blind and semi-blind signal separation techniques -signal processing techniques for analysis, enhancement, coding, synthesis and recognition of speech signals -direction-finding and beamforming techniques for audio and electromagnetic signals -analysis techniques for biomedical signals -baseband signal processing techniques for transmission and reception of communication signals -signal processing techniques for data hiding and audio watermarking -sparse signal processing and compressive sensing

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Engineering, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Computer Science and Engineering, ensuring accessibility and quality in research dissemination.

This journal requires an Article Processing Charge (APC) to support open access publishing, covering peer review, editing, and distribution. The current APC is 2,490.00 USD. Learn more.

Explore journals without APCs for alternative publishing options.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Review of noise removal techniques in ECG signals

  Citation: 234

  Authors: Shubhojeet, Rini Smita, Ram Narayan, Lalita, Deepak Kumar

• Recursive coupled projection algorithms for multivariable output‐error‐like systems with coloured noises

  Citation: 172

  Authors: Jian, Hao, Xiao, Qinyao, Feng, Yufang, Jie

• Unreliability of frequency-domain approximation in recognising chaos in fractional-order systems

  Citation: 139

  Authors: M.S., M.

• Parameter estimation algorithms for dynamical response signals based on the multi‐innovation theory and the hierarchical principle

  Citation: 128

  Authors: Ling, Feng

• Doppler signatures of radar backscattering from objects with micro-motions

  Citation: 124

  Authors: V.C.

• Learning deep features to recognise speech emotion using merged deep CNN

  Citation: 120

  Authors: Jianfeng, Xia, Lijiang

• Cubature quadrature Kalman filter

  Citation: 113

  Authors: Shovan

• Electrocardiogram signal denoising using non‐local wavelet transform domain filtering

  Citation: 105

  Authors: Santosh Kumar, Rohit, Prabin Kumar

• Acoustic vector sensor: reviews and future perspectives

  Citation: 93

  Authors: Jiuwen, Jun, Jianzhong, Xiaoping

• Event‐triggered <i> H _∞ </i> filtering for networked Takagi–Sugeno fuzzy systems with asynchronous constraints

  Citation: 89

  Authors: Jin, Chen