MERL - Mitsubishi Electric Research Laboratories

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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.

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  • Researchers

  • Awards

    •  AWARD   Excellent Presentation Award
      Date: January 25, 2021
      Awarded to: Takenori Sumi, Yukimasa Nagai, Jianlin Guo, Philip Orlik, Tatsuya Yokoyama, Hiroshi Mineno
      MERL Contacts: Jianlin Guo; Philip Orlik
      Research Areas: Communications, Machine Learning, Signal Processing
      Brief
      • MELCO and MERL researchers have won "Excellent Presentation Award" at the IPSJ/CDS30 (Information Processing Society of Japan/Consumer Devices and Systems 30th conferences) held on January 25, 2021. The paper titled "Sub-1 GHz Coexistence Using Reinforcement Learning Based IEEE 802.11ah RAW Scheduling" addresses coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. This paper proposes a novel method to allocate IEEE 802.11 RAW time slots using a Q-Learning technique. MERL and MELCO have been leading IEEE 802.19.3 coexistence standard development and this paper is a good candidate for future standard enhancement. The authors are Takenori Sumi, Yukimasa Nagai, Jianlin Guo, Philip Orlik, Tatsuya Yokoyama and Hiroshi Mineno.
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    •  AWARD   Outstanding Presentation Award at the 28th Conference of Information Processing Society of Japan/Consumer Device & Systems
      Date: October 20, 2020
      Awarded to: Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik, Hiroshi Mineno
      MERL Contacts: Jianlin Guo; Philip Orlik
      Research Areas: Communications, Optimization, Signal Processing
      Brief
      • MELCO and MERL researchers have won "Outstanding Presentation Award" at 28th Conference of Information Processing Society of Japan (IPSJ)/Consumer Device & Systems held on September 29-30, 2020. The paper titled "IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1 GHz Frequency Bands" reports IEEE 802.19.3 standard development on coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. MERL and MELCO have been leading this standard development and made major technical contributions, which propose methods to mitigate interference in smart meter systems. The authors are Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik and Hiroshi Mineno.
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    •  AWARD   Best Paper AWARD at International Workshop on Informatics (IWIN) 2020
      Date: September 11, 2020
      Awarded to: Yukimasa Nagai, Jianlin Guo, Takenori Sumi, Philip Orlik, Hiroshi Mineno
      MERL Contact: Jianlin Guo
      Research Areas: Communications, Signal Processing
      Brief
      • MELCO and MERL researchers have won one of two Best Paper Awards at International Workshop on Informatics (IWIN) 2020. The paper titled 'Hybrid CSMA/CA for Sub-1 GHz Frequency Band Coexistence of IEEE 802.11ah and IEEE 802.15.4g', reports research on the severity of interference between IEEE 802.11ah and IEEE 802.15.4g based networks and also proposes methods to mitigate this interference in smart meter systems. This research reported in this paper has also informed several of MELCO/MERL's contributions to the IEEE P802.19.3 task group which is developing standards to allow for improved coexistence in outdoor metering systems. Authors are Yukimasa Nagai, Jianlin Guo, Takenori Sumi, Philip Orlik and Hiroshi Mineno.
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  • News & Events

    •  NEWS   Keynote Speech by Dr. Petros Boufounos
      Date: August 5, 2021
      MERL Contact: Petros Boufounos
      Research Areas: Computational Sensing, Signal Processing
      Brief
      • MERL's Distinguished Researcher Dr. Petros Boufounos is the keynote speaker for the Center for Advanced Signal and Image Sciences (CASIS) 25th Annual Workshop on Aug. 5, 2021, with talk titled, "The Computational Sensing Revolution in Array Processing."
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    •  NEWS   MERL Congratulates Recipients of 2022 IEEE Technical Field Awards in Signal Processing
      Date: July 26, 2021
      MERL Contacts: Petros Boufounos; Jonathan Le Roux; Philip Orlik; Anthony Vetro
      Research Areas: Signal Processing, Speech & Audio
      Brief
      • IEEE has announced that the recipients of the 2022 IEEE James L. Flanagan Speech and Audio Processing Award will be Hervé Bourlard (EPFL/Idiap Research Institute) and Nelson Morgan (ICSI), "For contributions to neural networks for statistical speech recognition," and the recipient of the 2022 IEEE Fourier Award for Signal Processing will be Ali Sayed (EPFL), "For contributions to the theory and practice of adaptive signal processing." More details about the contributions of Prof. Bourlard and Prof. Morgan can be found in the announcements by ICSI and EPFL, and those of Prof. Sayed in EPFL's announcement. Mitsubishi Electric Research Laboratories (MERL) has recently become the new sponsor of these two prestigious awards, and extends our warmest congratulations to all of the 2022 award recipients.

        The IEEE Board of Directors established the IEEE James L. Flanagan Speech and Audio Processing Award in 2002 for outstanding contributions to the advancement of speech and/or audio signal processing, while the IEEE Fourier Award for Signal Processing was established in 2012 for outstanding contribution to the advancement of signal processing, other than in the areas of speech and audio processing. Both awards have recognized the contributions of some of the most renowned pioneers and leaders in their respective fields. MERL is proud to support the recognition of outstanding contributions to the signal processing field through its sponsorship of these awards.
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  • Research Highlights

  • Internships

    • SP1542: Research in Computational Sensing

      The Computational Sensing team at MERL is seeking motivated and qualified individuals to assist in the development of computational methods for a variety of sensing applications. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, learning for inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/sonar imaging, sensing of dynamical systems, or wave-based inversion. Experience with experimentally measured data is desirable. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • SP1475: Advanced Signal Processing for Metasurface

      MERL is seeking a highly motivated, qualified intern to join an internship program. The ideal candidate will be expected to carry out research on Advanced Signal Processing for Metasurface. The candidate is expected to develop innovative signal processing for metasurface aided various applications. Candidates should have strong knowledge about electromagnetic field analysis for metasurface, passive beamforming, interference mitigation, and channel estimation. Proficient programming skills with Python, MATLAB, and C++, and strong mathematical analysis will be additional assets to this position. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply. The expected duration of the internship is 3-6 months, with a flexible start date in 2020. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • CA1519: Estimation for High-Precision Positioning

      MERL is seeking a highly motivated candidate for development of next-generation high-precision positioning methods for autonomous systems applications, e.g., autonomous driving. The candidate will work with the Control for Autonomy team and the Signal Processing group in developing satellite-based positioning methods using information from multiple sources. Previous experience with at least some of the Bayesian inference, distributed estimation, satellite navigation systems, is highly desirable. Solid knowledge in MATLAB is required, working experience in C/C++ is desired, and previous experience with satellite navigation packages such as RTKLib is a merit. PhD candidates meeting the above requirements are encouraged to apply. The expected duration of the internship is 3-6 months with flexible start date. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.


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  • Recent Publications

    •  Wang, P., Koike-Akino, T., Ma, R., Orlik, P.V., Yamashita, G., Tsujita, W., Nakajima, M., "Learning-Based THz Multi-Layer Imaging for High-Capacity Positioning", International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), November 2021.
      BibTeX TR2021-098 PDF
      • @inproceedings{Wang2021nov,
      • author = {Wang, Perry and Koike-Akino, Toshiaki and Ma, Rui and Orlik, Philip V. and Yamashita, Genki and Tsujita, Wataru and Nakajima, M.},
      • title = {Learning-Based THz Multi-Layer Imaging for High-Capacity Positioning},
      • booktitle = {International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)},
      • year = 2021,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2021-098}
      • }
    •  Koike-Akino, T., Wang, Y., Kojima, K., Parsons, K., Yoshida, T., "Zero-Multiplier Sparse DNN Equalization for Fiber-Optic QAM Systems with Probabilistic Amplitude Shaping", European Conference on Optical Communication (ECOC), September 2021.
      BibTeX TR2021-110 PDF
      • @inproceedings{Koike-Akino2021sep,
      • author = {Koike-Akino, Toshiaki and Wang, Ye and Kojima, Keisuke and Parsons, Kieran and Yoshida, Tsuyoshi},
      • title = {Zero-Multiplier Sparse DNN Equalization for Fiber-Optic QAM Systems with Probabilistic Amplitude Shaping},
      • booktitle = {European Conference on Optical Communication (ECOC)},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-110}
      • }
    •  Skvortcov, P., Koike-Akino, T., Millar, D.S., Kojima, K., Parsons, K., "Dual Coding Concatenation for Burst-Error Correction in Probabilistic Amplitude Shapin", European Conference on Optical Communication (ECOC), September 2021.
      BibTeX TR2021-111 PDF
      • @inproceedings{Skvortcov2021sep2,
      • 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 Shapin},
      • booktitle = {European Conference on Optical Communication (ECOC)},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-111}
      • }
    •  Skvortcov, P., Millar, D.S., Phillips, I., Forysiak, W., Koike-Akino, T., Kojima, K., Parsons, K., "Experimental Analysis of Mismatched Soft-Demapping for Probabilistic Shaping in Short-Reach Nonlinear Transmission", European Conference on Optical Communication (ECOC), September 2021.
      BibTeX TR2021-109 PDF
      • @inproceedings{Skvortcov2021sep,
      • author = {Skvortcov, Pavel and Millar, David S. and Phillips, Ian and Forysiak, Wladek and Koike-Akino, Toshiaki and Kojima, Keisuke and Parsons, Kieran},
      • title = {Experimental Analysis of Mismatched Soft-Demapping for Probabilistic Shaping in Short-Reach Nonlinear Transmission},
      • booktitle = {European Conference on Optical Communication (ECOC)},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-109}
      • }
    •  Liu, B., Guo, J., Koike-Akino, T., Wang, Y., Kim, K.J., Parsons, K., Orlik, P.V., Hashimoto, S., Yuan, J., "Anomaly Detection and Diagnosis Using Pre-Processing and Time-Delay Autoencoder", IEEE International conference on emerging technologies and factory automation, September 2021.
      BibTeX TR2021-107 PDF
      • @inproceedings{Liu2021sep,
      • author = {Liu, Bryan and Guo, Jianlin and Koike-Akino, Toshiaki and Wang, Ye and Kim, Kyeong Jin and Parsons, Kieran and Orlik, Philip V. and Hashimoto, Shigeru and Yuan, Jinhong},
      • title = {Anomaly Detection and Diagnosis Using Pre-Processing and Time-Delay Autoencoder},
      • booktitle = {IEEE International conference on emerging technologies and factory automation},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-107}
      • }
    •  Koike-Akino, T., Wang, Y., "Evolution of Polar Coding", IEEE International Symposium on Topics in Coding (ISTC), August 2021.
      BibTeX TR2021-104 PDF
      • @inproceedings{Koike-Akino2021aug,
      • author = {Koike-Akino, Toshiaki and Wang, Ye},
      • title = {Evolution of Polar Coding},
      • booktitle = {IEEE International Symposium on Topics in Coding (ISTC)},
      • year = 2021,
      • month = aug,
      • url = {https://www.merl.com/publications/TR2021-104}
      • }
    •  Greiff, M., Berntorp, K., Di Cairano, S., Kim, K.J., "Mixed-Integer Linear Regression Kalman Filters for GNSS Positioning", IEEE Conference on Control Technology and Applications (CCTA), August 2021.
      BibTeX TR2021-090 PDF
      • @inproceedings{Greiff2021aug,
      • author = {Greiff, Marcus and Berntorp, Karl and Di Cairano, Stefano and Kim, Kyeong Jin},
      • title = {Mixed-Integer Linear Regression Kalman Filters for GNSS Positioning},
      • booktitle = {IEEE Conference on Control Technology and Applications (CCTA)},
      • year = 2021,
      • month = aug,
      • url = {https://www.merl.com/publications/TR2021-090}
      • }
    •  Wang, Y., Aeron, S., Rakin, A.S., Koike-Akino, T., Moulin, P., "Robust Machine Learning via Privacy/Rate-Distortion Theory", IEEE International Symposium on Information Theory (ISIT), DOI: 10.1109/​ISIT45174.2021.9517751, July 2021.
      BibTeX TR2021-082 PDF Video Presentation
      • @inproceedings{Wang2021jul,
      • author = {Wang, Ye and Aeron, Shuchin and Rakin, Adnan S and Koike-Akino, Toshiaki and Moulin, Pierre},
      • title = {Robust Machine Learning via Privacy/Rate-Distortion Theory},
      • booktitle = {IEEE International Symposium on Information Theory (ISIT)},
      • year = 2021,
      • month = jul,
      • publisher = {IEEE},
      • doi = {10.1109/ISIT45174.2021.9517751},
      • isbn = {978-1-5386-8210-4},
      • url = {https://www.merl.com/publications/TR2021-082}
      • }
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