Circuits, Systems, and Signal Processing

Aims & Scope

Rapid developments in the analog and digital processing of signals for communication, control, and computer systems have made the theory of electrical circuits and signal processing a burgeoning area of research and design.

The aim of Circuits, Systems, and Signal Processing (CSSP) is to help meet the needs of outlets for significant research papers and state-of-the-art review articles in the area.

The scope of the journal is broad, ranging from mathematical foundations to practical engineering design.

It encompasses, but is not limited to, such topics as linear and nonlinear networks, distributed circuits and systems, multi-dimensional signals and systems, analog filters and signal processing, digital filters and signal processing, statistical signal processing, multimedia, computer aided design, graph theory, neural systems, communication circuits and systems, and VLSI signal processing.

The Editorial Board is international, and papers are welcome from throughout the world.

The journal is devoted primarily to research papers, but survey, expository, and tutorial papers are also published.

Circuits, Systems, and Signal Processing (CSSP) is published twelve times annually.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2
2024	1.80

Journal Rank

Year	Value
2024	14124

Journal Citation Indicator

Year	Value
2024	2464

SJR (SCImago Journal Rank)

Year	Value
2024	0.387

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	68

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Abstracting & Indexing

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

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

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

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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.

• A survey of linear singular systems

  Citation: 1060

  Authors: F. L.

• A Deep Learning-Based Framework for Automatic Brain Tumors Classification Using Transfer Learning

  Citation: 509

  Authors: Arshia, Saeeda, Muhammad Imran, Faiza, Muhammad

• Fast Normalized Cross-Correlation

  Citation: 390

  Authors: Jae-Chern, Tae Hee

• An overview of morphological filtering

  Citation: 314

  Authors: Jean, Luc

• Seasonal Crops Disease Prediction and Classification Using Deep Convolutional Encoder Network

  Citation: 228

  Authors: Aditya, Gurinder, Deepak, Ashish, Shrasti, Victor Hugo C.

• Eigenstructure methods for direction finding with sensor gain and phase uncertainties

  Citation: 199

  Authors: Anthony J., Benjamin

• Prediction error estimation methods

  Citation: 199

  Authors: Lennart

• Fractional-Order RC and RL Circuits

  Citation: 186

  Authors: A. G., K. N.

• Multi-object Detection and Tracking (MODT) Machine Learning Model for Real-Time Video Surveillance Systems

  Citation: 174

  Authors: M.

• Decomposition- and Gradient-Based Iterative Identification Algorithms for Multivariable Systems Using the Multi-innovation Theory

  Citation: 171

  Authors: Lijuan, Feng

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