The ISPLab pursues frontier and original research with research expertise covering the design/theory, realization, and applications of:
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University of Windsor
We are currently recruiting new Ph.D., M.A.Sc., and B.A.Sc. students who are interested in intelligent signal processing system design and its real-time applications. Students with prior successful software implementation experience in smart-phone-based real-time digital signal processing are preferred.
The ISPLab accepts Ph.D. students, and M.A.Sc. students under the supervision of Dr. H. K. Kwan. We offer the needed financially support to a highly qualified and motivated graduate applicant with a suitable academic background and a strong interest to complete a Ph.D. (or M.A.Sc.) research in our area of specialization. Our Ph.D. and M.A.Sc. students are regular full-time students in the Department of Electrical and Computer Engineering of the Faculty of Engineering and are admitted under the normal University of Windsor's graduate admission procedures. We welcome international and national collaborations with other researchers (including visiting scholars and postdoctoral fellows) of common research interests.
Our research is supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC).
B. Research Demos
Demo 1: Huabin Wang, Rui Cheng, Jian Zhou, Liang Tao, Hon Keung Kwan, "Multistage model for robust face alignment using deep neural networks," Cognitive Computation, Regular paper, accepted January 29, 2021. Preprint arXiv:2002.01075, 2020.
- Digital filters (including FIR, IIR, and lattice digital filters; AR and ARMA lattice modeling; variable frequency filters, and variable fractional delay filters; adaptive filters, and sigmoid adaptive filters; chaotic digital filters; fuzzy filters; canonic, multiplierless, systolic, and multi-GHz digital filters).
- Neural networks (including deep and shadow neural networks, fuzzy neural networks, recurrent associative memory; multiplierless and systolic neural networks).
- Digital signal processing (including real-valued and complex-valued discrete Gabor transforms, parallel realization; sensor network localization; genomic signal processing).
- Optimization algorithms (including evolutionary, gradient, convex, and multi-objective optimization algorithms).
Demo 2: Jian Zhou, Yuting Hu, Hailun Lian, Huabin Wang, Liang Tao, Hon Keung Kwan, "Multimodal voice conversion under adverse environment using a deep convolutional neural network," IEEE Access, volume 7, pages 170878 - 170887, 26 November 2019, DOI: 10.1109/ACCESS.2019.2955982
C. About UWindsor Engineering Research