IEEE Transactions on Signal Processing

Scope

The IEEE Transactions on Signal Processing (TSP) covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term "signal" includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.

The scope is reflected in the EDICS: the Editors` Information Classification Scheme.
The Transactions publish original, timely and significant contributions. Submissions must be previously unpublished and may not be under considerations elsewhere. Technical papers are submitted via Manuscript Central (see Author`s Instructions). Please consider the journal with the most appropriate scope for your submission.

Abstracts and indexing

The Transactions is listed in AMS MathSciNet (Mathematical Reviews Database), Current Contents (Engineering, Computing & Technology, Electronics & Telecommunications Collection), CompuMath citation index, EI Compendex, IEE INSPEC, ISI Science Citation Index, ISI SciSearch, Scitation Research Alerts, PubMed, Medline.

Reproducible research

The Transactions encourages authors to make their publications reproducible by making all information needed to reproduce the presented results available online. This typically requires publishing the code and data used to produce the publication`s figures and tables on a website; see the supplemental materials section of the information for authors. It gives other researchers easier access to the work, and facilitates fair comparisons.

Multimedia content

It is now possible to submit for review and publish in Xplore supporting multimedia material such as speech samples, images, movies, matlab code etc. A multimedia graphical abstract can also be displayed along with the traditional text. More information is available under Multimedia Materials at the IEEE Author Center.

TSP Volume 70 | 2022

Widely Linear Maximum Complex Correntropy Criterion Affine Projection Algorithm and Its Performance Analysis

Recently, affine projection algorithm has been extensively studied in the Gaussian noise environment. However, the performance of affine projection algorithm will deteriorate rapidly in the presence of impulsive noise and other non-Gaussian noise. To address this issue, this paper proposes a novel affine projection algorithm based on the complex Gaussian kernel function, called widely linear maximum complex correntropy criterion affine projection algorithm (WL-MCCC-APA).

Read more

TSP Volume 69 | 2021

Particle Filtering for Nonlinear/Non-Gaussian Systems With Energy Harvesting Sensors Subject to Randomly Occurring Sensor Saturations

In this paper, the particle filtering problem is investigated for a class of nonlinear/non-Gaussian systems with energy harvesting sensors subject to randomly occurring sensor saturations (ROSSs). The random occurrences of the sensor saturations are characterized by a series of Bernoulli distributed stochastic variables with known probability distributions.

Read more

Filtering in Pairwise Markov Model With Student's t Non-Stationary Noise With Application to Target Tracking

Hidden Markov models are widely used for target tracking, where the process and measurement noises are usually modeled as independent Gaussian distributions for mathematical simplicity. However, the independence and Gaussian assumptions do not always hold in practice. For example, in a typical target tracking application, a radar is utilized to track a non-cooperative target.

Read more