The Digital Signal Processing and Artificial Intelligence for Automatic Learning follows triple blind review system where each submission undergoes review by a minimum of three domain experts. The experts are selected based on their domain knowledge and research experience including their publication and citation profile. A paper will be accepted ONLY if ALL the three reviewers recommend the acceptance with consistency. The journal use a very strong review scale which includes originality, novelty, methodological strength, experiments, data, inferences, analysis, presentation and language. The authors are clearly informed that the journal uses a very strong anti-plagiarism policy. The plagiarism is checked at many levels by different team which includes editors, sub-editors, reviewers and plagiarism detection experts. The journal requires the reviewers to recommend any one of the four decisions. It includes clear acceptance, major revision, minor revision and rejection. It is found that in the last ten years the journal has not received any clear acceptance from the reviewers. The papers which are recommended with major revisions are not accepted.
REVIEWERS:
Vladik Kreinovich (University of Texas at El Paso, USA). http://www.cs.utep.edu/vladik/
Luc Longpré, (University of Texas at El Paso, USA). http://expertise.utep.edu/profiles/longpre
Nigel Ward, (University of Texas at El Paso, USA). http://www.cs.utep.edu/nigel/
Zbigniew Lipiński (Opole University, Poland). http://www.math.uni.opole.pl/~zlipinski/
Salvador Cervantes Alvarez, (University of Guadalajara, Mexico)
Adriana Mexicano Santoyo, (Technological Institute of Ciudad Victoria, Mexico)
Ke Liao (University of Kansas, USA)
Mohamed Elgendi (University of British Columbia, Canada)
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