Signal Processing
Acquisition and processing of information.
Our research in the area of signal processing encompasses a wide range of work in the areas of communications, sensing, estimation, localization, and speech and visual information processing. We explore novel approaches for signal acquisition and coding, methods to filter and recover signals in the presence of noise and other degrading factors, and techniques that infer meaning from the processed signals.
Quick Links
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Researchers
Toshiaki
Koike-Akino
Philip V.
Orlik
Kieran
Parsons
Pu
(Perry)
Wang
Ye
Wang
Kyeong Jin
(K.J.)
Kim
Karl
Berntorp
Petros T.
Boufounos
Hassan
Mansour
Bingnan
Wang
Stefano
Di Cairano
Jianlin
Guo
Yebin
Wang
Dehong
Liu
Koon Hoo
Teo
Mouhacine
Benosman
Marcus
Greiff
Devesh K.
Jha
Chungwei
Lin
Yanting
Ma
Hongbo
Sun
Jinyun
Zhang
Matthew E.
Brand
Marcel
Menner
Anthony
Vetro
Ankush
Chakrabarty
Suhas
Lohit
Tim K.
Marks
Rien
Quirynen
Avishai
Weiss
William S.
Yerazunis
Jose
Amaya
Jonathan
Le Roux
Joshua
Rapp
Huifang
Sun
Wataru
Tsujita
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Awards
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AWARD Joshua Rapp wins Best Dissertation Award from the IEEE Signal Processing Society Date: December 20, 2021
Awarded to: Joshua Rapp
MERL Contact: Joshua Rapp
Research Areas: Computational Sensing, Signal ProcessingBrief- Joshua Rapp has won the 2021 Best PhD Dissertation Award from the IEEE Signal Processing Society.
The award recognizes a PhD thesis completed on a signal processing subject within the past three years for its relevant work in signal processing while stimulating further research in the field.
Dr. Rapp completed his PhD at Boston University in 2020 with a thesis entitled "Probabilistic Modeling for Single-Photon Lidar." The dissertation tackles challenges of the acquisition and processing of 3D depth maps reconstructed from time-of-flight data captured one photon at a time.
The award will be presented at the 2022 IEEE International Conference on Image Processing (ICIP) in France.
- Joshua Rapp has won the 2021 Best PhD Dissertation Award from the IEEE Signal Processing Society.
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AWARD Petros Boufounos Elevated to IEEE Fellow Date: January 1, 2022
Awarded to: Petros T. Boufounos
MERL Contact: Petros T. Boufounos
Research Areas: Computational Sensing, Signal ProcessingBrief- MERL’s Petros Boufounos has been elevated to IEEE Fellow, effective January 2022, for “contributions to compressed sensing.”
IEEE Fellow is the highest grade of membership of the IEEE. It honors members with an outstanding record of technical achievements, contributing importantly to the advancement or application of engineering, science and technology, and bringing significant value to society. Each year, following a rigorous evaluation procedure, the IEEE Fellow Committee recommends a select group of recipients for elevation to IEEE Fellow. Less than 0.1% of voting members are selected annually for this member grade elevation.
- MERL’s Petros Boufounos has been elevated to IEEE Fellow, effective January 2022, for “contributions to compressed sensing.”
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AWARD Toshiaki Koike-Akino elected Fellow of Optica Date: November 18, 2021
Awarded to: Toshiaki Koike-Akino
MERL Contact: Toshiaki Koike-Akino
Research Areas: Communications, Electronic and Photonic Devices, Signal ProcessingBrief- Toshiaki Koike-Akino's research activities in communications, error control coding and optical technologies at MERL have earned him election as a Fellow Member of Optica (formerly OSA), the foremost professional association in optics and photonics worldwide. Fellow membership in Optica is limited to no more than ten percent of the membership and is reserved for members who have served with distinction in the advancement of optics and photonics. Koike-Akino is one of 106 members from 24 countries in Optica’s 2022 Fellows Class, elected during the Board of Directors of Optica meeting held on 2nd of November, 2021.
“Congratulations to the 2022 Optica Fellows,” said 2021 President Connie Chang-Hasnain, University of California, Berkeley, USA. “These members exemplify what it means to be a leader in optics and photonics. Your election, by your peers, confirms the important contributions made within our field. Thank you for your dedication to Optica, and for advancing the science of light.”
Koike-Akino's elevation to Fellow is specifically “for outstanding and innovative contributions to R&D in enabling technologies for optical communications, including nonlinear equalizers, high-dimensional modulations, and FEC (Forward Error Correction),” said Meredith Smith, Director, Optica Awards and Honors Office. "Again, congratulations on joining this esteemed group of Optica members."
About Optica
Optica (formerly OSA) is dedicated to promoting the generation, application, archiving and dissemination of knowledge in optics and photonics worldwide. Founded in 1916, it is the leading organization for scientists, engineers, business professionals, students and others interested in the science of light. Optica’s renowned publications, meetings, online resources and in-person activities fuel discoveries, shape real-life applications and accelerate scientific, technical and educational achievement.
- Toshiaki Koike-Akino's research activities in communications, error control coding and optical technologies at MERL have earned him election as a Fellow Member of Optica (formerly OSA), the foremost professional association in optics and photonics worldwide. Fellow membership in Optica is limited to no more than ten percent of the membership and is reserved for members who have served with distinction in the advancement of optics and photonics. Koike-Akino is one of 106 members from 24 countries in Optica’s 2022 Fellows Class, elected during the Board of Directors of Optica meeting held on 2nd of November, 2021.
See All Awards for Signal Processing -
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News & Events
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EVENT MERL's Virtual Open House 2022 Date & Time: Monday, December 12, 2022; 1:00pm-5:30pm ET
Location: Mitsubishi Electric Research Laboratories (MERL)/Virtual
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital VideoBrief- Join MERL's virtual open house on December 12th, 2022! Featuring a keynote, live sessions, research area booths, and opportunities to interact with our research team. Discover who we are and what we do, and learn about internship and employment opportunities.
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NEWS MERL Researcher Kyeong Jin Kim organizes the second international workshop in 2023 IEEE International Conference on Communications (ICC). Date: May 28, 2023 - June 1, 2023
Where: Rome, Italy
MERL Contact: Kyeong Jin (K.J.) Kim
Research Areas: Artificial Intelligence, Communications, Computational Sensing, Machine Learning, Signal ProcessingBrief- Kyeong Jin Kim, a Senior Principal Research Scientist in the Connectivity & Information Processing Team, organizes the second international workshop in 2023 IEEE International Conference on Communications (ICC). The workshop is titled, "Industrial Private 5G-and-beyond Wireless Networks," and aims to bring researchers for technical discussion on fundamental and practically relevant questions to many emerging challenges in industrial private wireless networks. This workshop is also being organized with the help of other researchers from industry and academia such as Huawei Technology, University of South Florida, Aalborg University, Jinan University, and South China University of Technology. IEEE ICC is one of two IEEE Communications Society's flagship conferences.
See All News & Events for Signal Processing -
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Research Highlights
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Internships
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MD1937: Mechanical vibration analysis
MERL is looking for a self-motivated intern to work on monitoring of motor drive system via vibration analysis. The ideal candidate would be a Ph.D. candidate in electrical engineering or mechanical engineering with solid research background in signal processing, vibration analysis, and mechanical system. Proficiency in Matlab or other related software is necessary. Experience in machine learning is a plus. The intern is expected to collaborate with MERL researchers to perform model simulation, data analysis, and prepare manuscripts for scientific publications. The total duration is anticipated to be 3 months and the start date is flexible. This internship requires work that can only be done at MERL.
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MD1897: Electric Motor Fault Detection
MERL is seeing a motivated and qualified individual to conduct research on electric machine fault analysis and detection. Ideal candidates should be Ph.D. students with solid background and publication record in one more research area: electric machine design, analysis, fault detection, and predictive maintenance. Research experiences on modeling and analysis of electric machines and fault detection are required. Hands-on experience with permanent magnet synchronous motor (PMSM) design, data analysis, and machine learning techniques are highly desirable. Start date for this internship is flexible and the duration is 3-6 months.
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CA1706: Perception-aware vehicle control
MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on planning and control algorithms accounting for perception of the uncertain surrounding environment. The ideal candidate is expected to be working towards a PhD with strong emphasis in control or planning algorithms, and to have interest and background in as many as possible of: predictive control algorithms for linear and nonlinear systems, stochastic constrained control, e.g., chance constraints, stochastic optimization, statistical estimation, perception system modeling, and vehicle modeling and control. Good programming skills in MATLAB, Python or C/C++ are required. The expected start of of the internship is in the late Spring/Early Summer 2022, for a duration of 3-6 months.
See All Internships for Signal Processing -
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Recent Publications
- , "Learning Occlusion-Aware Dense Correspondences for Multi-Modal Images", IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), November 2022.BibTeX TR2022-149 PDF
- @inproceedings{Shimoya2022nov,
- author = {Shimoya, Ryosuke and Morimoto, Tahashi and van Baar, Jeroen and Boufounos, Petros T. and Ma, Yanting and Mansour, Hassan},
- title = {Learning Occlusion-Aware Dense Correspondences for Multi-Modal Images},
- booktitle = {IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)},
- year = 2022,
- month = nov,
- url = {https://www.merl.com/publications/TR2022-149}
- }
- , "Dual Coding Concatenation for Burst-Error Correction in Probabilistic Amplitude Shaping", IEEE Journal of Lightwave Technology, DOI: 10.1109/JLT.2022.3178675, Vol. 40, No. 16, pp. 5502-5513, November 2022.BibTeX TR2022-145 PDF
- @article{Skvortcov2022nov,
- author = {Skvortcov, Pavel and Koike-Akino, Toshiaki and Millar, David S. and Kojima, Keisuke and Parsons, Kieran},
- title = {Dual Coding Concatenation for Burst-Error Correction in Probabilistic Amplitude Shaping},
- journal = {IEEE Journal of Lightwave Technology},
- year = 2022,
- volume = 40,
- number = 16,
- pages = {5502--5513},
- month = nov,
- doi = {10.1109/JLT.2022.3178675},
- issn = {1558-2213},
- url = {https://www.merl.com/publications/TR2022-145}
- }
- , "Improving Adversarial Robustness by Learning Shared Information", Pattern Recognition, November 2022.BibTeX TR2022-141 PDF
- @article{Yu2022nov,
- author = {Yu, Xi and Smedemark-Margulies, Niklas and Aeron, Shuchin and Koike-Akino, Toshiaki and Moulin, Pierre and Brand, Matthew E. and Parsons, Kieran and Wang, Ye},
- title = {Improving Adversarial Robustness by Learning Shared Information},
- journal = {Pattern Recognition},
- year = 2022,
- month = nov,
- url = {https://www.merl.com/publications/TR2022-141}
- }
- , "Incomplete Multi-view Domain Adaptation via Channel Enhancement and Knowledge Transfer", European Conference on Computer Vision (ECCV), October 2022.BibTeX TR2022-134 PDF
- @inproceedings{Xia2022oct,
- author = {Xia, Haifeng and Wang, Pu and Ding, Zhengming},
- title = {Incomplete Multi-view Domain Adaptation via Channel Enhancement and Knowledge Transfer},
- booktitle = {European Conference on Computer Vision (ECCV)},
- year = 2022,
- month = oct,
- url = {https://www.merl.com/publications/TR2022-134}
- }
- , "Distributed Radar Autofocus Imaging Using Deep Priors", IEEE International Conference on Image Processing (ICIP), October 2022.BibTeX TR2022-129 PDF Video
- @inproceedings{Mansour2022oct,
- author = {Mansour, Hassan and Lohit, Suhas and Boufounos, Petros T.},
- title = {Distributed Radar Autofocus Imaging Using Deep Priors},
- booktitle = {IEEE International Conference on Image Processing (ICIP)},
- year = 2022,
- month = oct,
- url = {https://www.merl.com/publications/TR2022-129}
- }
- , "Eccentricity Severity Estimation of Induction Machines using a Sparsity-Driven Regression Model", The Fourteenth Annual Energy Conversion Congress and Exposition, October 2022.BibTeX TR2022-126 PDF
- @inproceedings{Zheng2022oct,
- author = {Zheng, Xiangtian and Liu, Dehong and Inoue, Hiroshi and Kanemaru, Makoto},
- title = {Eccentricity Severity Estimation of Induction Machines using a Sparsity-Driven Regression Model},
- booktitle = {The Fourteenth Annual Energy Conversion Congress and Exposition},
- year = 2022,
- month = oct,
- url = {https://www.merl.com/publications/TR2022-126}
- }
- , "quEEGNet: Quantum AI for Biosignal Processing", IEEE Conference on Biomedical and Health Informatics (BHI), September 2022.BibTeX TR2022-121 PDF Video Presentation
- @inproceedings{Koike-Akino2022sep,
- author = {Koike-Akino, Toshiaki and Wang, Ye},
- title = {quEEGNet: Quantum AI for Biosignal Processing},
- booktitle = {IEEE Conference on Biomedical and Health Informatics (BHI)},
- year = 2022,
- month = sep,
- url = {https://www.merl.com/publications/TR2022-121}
- }
- , "X-Disco: Cross-technology Neighbor Discovery", IEEE International Conference on Sensing, Communication, and Networking, September 2022.BibTeX TR2022-119 PDF
- @inproceedings{Wang2022sep2,
- author = {Wang, Shuai and Guo, Jianlin and Wang, Pu and Parsons, Kieran and Orlik, Philip V. and Nagai, Yukimasa and Sumi, Takenori and Pathak, Parth and},
- title = {X-Disco: Cross-technology Neighbor Discovery},
- booktitle = {IEEE International Conference on Sensing, Communication, and Networking},
- year = 2022,
- month = sep,
- url = {https://www.merl.com/publications/TR2022-119}
- }
- , "Learning Occlusion-Aware Dense Correspondences for Multi-Modal Images", IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), November 2022.
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Videos
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Toshiaki Koike-Akino Gives Seminar Talk at IEEE Boston Photonics
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[MERL Seminar Series 2021] Deep probabilistic regression
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[MERL Seminar Series 2021] Reconfigurable Intelligent Surfaces for Wireless Communications
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Application of Deep Learning for Nanophotonic Device Design (Invited)
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Multiview Sensing with Unknown Permutations: An Optimal Transport Approach
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Imaging for inverse scattering in Reflection Tomography
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All Digital Transmitter
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Machine Learning Power Amplifier
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Polar Coding with Chemical Reaction Networks for Molecular Communications
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EMI reduction in PWM inverters using adaptive frequency modulated carriers
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Through-the-Wall Imaging
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Software Downloads
