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.

  • Researchers

  • Awards

    •  AWARD   MERL Researchers Won IEEE ICC Best Paper Award.
      Date: May 22, 2019
      Awarded to: Siriramya Bhamidipati, Kyeong Jin Kim, Hongbo Sun, Philip Orlik
      MERL Contacts: Kyeong Jin (K.J.) Kim; Hongbo Sun
      Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal Processing, Information Security
      Brief
      • MERL researchers, Kyeong Jin Kim, Hongbo Sun, Philip Orlik, along with lead author and former MERL intern Siriramya Bhamidipati were awarded the Smart Grid Symposium Best Paper Award at this year's International Conference on Communications (ICC) held in Shanghai, China. There paper titled "GPS Spoofing Detection and Mitigation in PMUs Using Distributed Multiple Directional Antennas," described a technique to rapidly detect and mitigate GPS timing attacks/errors via hardware (antennas) and signal processing (Kalman Filtering)
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    •  AWARD   MERL researcher wins IEEE Young Author Best Paper award
      Date: January 2, 2019
      Awarded to: Siheng Chen
      MERL Contact: Siheng Chen
      Research Area: Signal Processing
      Brief
      • MERL researcher, Siheng Chen, has won an IEEE Young Author Best Paper award for his paper entitled "Discrete Signal Processing on Graphs: Sampling Theory". This paper, published in the December 2015 issue of IEEE Transactions on Signal Processing, proposes a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory and shows that perfect recovery is possible for graph signals bandlimited under the graph Fourier transform. The award honors the authors of an especially meritorious paper dealing with a subject related to IEEE's technical scope and appearing in one if its journals within a three year window of eligibility.
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    •  AWARD   Former Intern Receives IBM Scientific Award Honorable Mention
      Date: January 16, 2019
      Awarded to: Daniel Dinis
      MERL Contact: Rui Ma
      Research Areas: Communications, Signal Processing
      Brief
      • Former MERL intern Daniel Dinis from University of Aveiro (UA), Portugal has received the 2018 IBM Scientific Award with Honorable Mention referring to the contributions on "Real-time Tunable Delta-sigma modulators for All-Digital RF Transmitters" in his Ph.D. study.

        The award-winning work includes research conducted under the supervision of Arnaldo Oliveira and José Neto Vieira, professors from the Department of Electronics and Information Technology (DETI) of the UA, as well as contributions made during Daniel's 7 month internship in 2017 at MERL.

        The ceremony for the presentation of the 28th IBM Scientific Prize took on January 16th, at the Noble Hall of the Superior Technical Institute. It was chaired by Marcelo Rebelo de Sousa, President of the Portuguese Republic.
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  • News & Events

    •  TALK   A Prospect in Wireless Connectivity Beyond 5G: Heterogeneity, Learning, Caution, and New Opportunities
      Date & Time: Thursday, May 7, 2020; 11:00 AM
      Speaker: Prof. Petar Popovski, Aalborg University, Denmark
      MERL Host: Toshiaki Koike-Akino
      Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal Processing, Information Security
      Brief
      • The wireless landscape evolves towards supporting a large population of connections for humans and machines with very diverse features and requirements. Perhaps the main motivation of 5G wireless systems is its flexibility to support heterogeneous connectivity requirements: enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). However, this classification is rather limited and is currently undergoing a revision within the research community. The first part of this talk will discuss how this heterogeneity can be revised and which opportunities it opens with respect to spectrum usage. The second part of the talk will deal with performance guarantees of wireless services and, specifically, ultra-reliable communication and outline the importance of machine learning in that context. The final part of the talk will provide a broader view on the evolution of wireless connectivity, including aspects that are implied by the resistance to the deployment of 5G, but also the new opportunities that can transform the way we build and utilize connected systems.
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    •  NEWS   MERL Researcher Kyeong Jin Kim serves as a lead guest editor of IEEE Journal on Selected Topics in Signal Processing
      Date: April 29, 2020
      Where: N/A
      MERL Contact: Kyeong Jin (K.J.) Kim
      Research Areas: Communications, Optimization, Signal Processing, Information Security
      Brief
      • Kyeong Jin Kim, a Senior Principal Research Scientist in the Signal Processing Group, will serve as lead guest editor for the upcoming JSTSP issue on, "Advanced Signal Processing for Local and Private 5G Networks." The issue is also being organized with the help of other researchers and investigators from leading organizations such as Memorial University, Nokia Bell Laboratories, Princeton University, Aalborg University, Jinan University, and South China University of Technology. This special issue aims to capture the latest research activities in local and private 5G networks from the signal processing perspective and is targeted for publication January 2022.
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  • Research Highlights

  • Internships

    • MD1398: Electrical machine modeling

      MERL is looking for a self-motivated intern to work on electrical machine modelling and signal processing. The ideal candidate would be a Ph.D. candidate in electrical engineering with solid research background in electrical machines, signal processing, and electrical circuit analysis. Experience in transient analysis of electrical machines is desirable. Proficiency in MATLAB and simulink is necessary. The intern is expected to collaborate with MERL researchers to build models, develop algorithms, and prepare manuscripts for scientific publications. The total duration is 3 months.

    • MD1441: Advanced Phased Array Transceiver

      MERL is looking for a highly motivated, and qualified individual to join our internship program of advanced phased array research. The ideal candidate should be a senior Ph.D. student with rich experience in beam forming technologies. Knowledge of wireless communication, transceiver architecture, and digital signal processing, FPGA and/or Matlab programming skills are required. RF circuits knowledge will be a plus. Duration is 3-6 months with a flexible start date.

    • SP1419: Simulation of Multimodal Sensors

      MERL is seeking a motivated intern to assist in generating simulated multimodal data for machine learning applications. The project involves integrating several existing software components to generate optical and radar data in a variety of sensing scenarios, and executing the simulations under a variety of conditions. The ideal candidate should have experience with C++, Python, and scripting methods. Some knowledge or experience with Blender, computer graphics, and computer vision would be preferred, but is not required. Project duration is flexible in the range of 1-2 months. Intern has the choice of part-time or full-time occupation and may start immediately.


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  • Openings


    See All Openings at MERL
  • Recent Publications

    •  Chen, S., Zhang, N., Sun, H., "Collaborative Localization Based on Traffic Landmarks for Autonomous Driving", IEEE International Symposium on Circuits and Systems (ISCAS), May 2020.
      BibTeX TR2020-064 PDF
      • @inproceedings{Chen2020may,
      • author = {Chen, Siheng and Zhang, Ningxiao and Sun, Huifang},
      • title = {Collaborative Localization Based on Traffic Landmarks for Autonomous Driving},
      • booktitle = {IEEE International Symposium on Circuits and Systems (ISCAS)},
      • year = 2020,
      • month = may,
      • url = {https://www.merl.com/publications/TR2020-064}
      • }
    •  Fujihashi, T., Koike-Akino, T., Watanabe, T., Orlik, P.V., "Overhead Reduction in Graph-Based Point Cloud Delivery", IEEE International Conference on Communications (ICC), May 2020.
      BibTeX TR2020-061 PDF Video
      • @inproceedings{Fujihashi2020may2,
      • author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi and Orlik, Philip V.},
      • title = {Overhead Reduction in Graph-Based Point Cloud Delivery},
      • booktitle = {IEEE International Conference on Communications (ICC)},
      • year = 2020,
      • month = may,
      • url = {https://www.merl.com/publications/TR2020-061}
      • }
    •  Sun, H., Wang, P., Pajovic, M., Koike-Akino, T., Orlik, P.V., Taira, A., Nakagawa, K., "Fingerprinting-Based Outdoor Localization with 28-GHz Channel Measurement: A Field Study", IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), May 2020.
      BibTeX TR2020-056 PDF
      • @inproceedings{Sun2020may,
      • author = {Sun, Haijian and Wang, Pu and Pajovic, Milutin and Koike-Akino, Toshiaki and Orlik, Philip V. and Taira, Akinori and Nakagawa, Kenji},
      • title = {Fingerprinting-Based Outdoor Localization with 28-GHz Channel Measurement: A Field Study},
      • booktitle = {IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)},
      • year = 2020,
      • month = may,
      • url = {https://www.merl.com/publications/TR2020-056}
      • }
    •  Fujihashi, T., Koike-Akino, T., Watanabe, T., Orlik, P.V., "High-Quality Soft Image Delivery with Deep Image Denoising", IEEE International Conference on Communications (ICC), May 2020.
      BibTeX TR2020-060 PDF Video
      • @inproceedings{Fujihashi2020may,
      • author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi and Orlik, Philip V.},
      • title = {High-Quality Soft Image Delivery with Deep Image Denoising},
      • booktitle = {IEEE International Conference on Communications (ICC)},
      • year = 2020,
      • month = may,
      • url = {https://www.merl.com/publications/TR2020-060}
      • }
    •  Bhamidipati, S., Kim, K.J., Sun, H., Orlik, P.V., "Artificial Intelligence-Based Distributed Belief Propagation and Recurrent Neural Network Algorithm for Wide-Area Monitoring Systems", IEEE Network, May 2020.
      BibTeX TR2020-058 PDF
      • @article{Bhamidipati2020may,
      • author = {Bhamidipati, Sriramya and Kim, Kyeong Jin and Sun, Hongbo and Orlik, Philip V.},
      • title = {Artificial Intelligence-Based Distributed Belief Propagation and Recurrent Neural Network Algorithm for Wide-Area Monitoring Systems},
      • journal = {IEEE Network},
      • year = 2020,
      • month = may,
      • url = {https://www.merl.com/publications/TR2020-058}
      • }
    •  Zhang, S., Wang, B., Kanemaru, M., Lin, C., Liu, D., Habetler, T., "Model-Based Analysis and Quantification of Bearing Faults in Induction Machines", IEEE Transactions on Industry Applications, May 2020.
      BibTeX TR2020-059 PDF
      • @article{Zhang2020may,
      • author = {Zhang, Shen and Wang, Bingnan and Kanemaru, Makoto and Lin, Chungwei and Liu, Dehong and Habetler, Thomas},
      • title = {Model-Based Analysis and Quantification of Bearing Faults in Induction Machines},
      • journal = {IEEE Transactions on Industry Applications},
      • year = 2020,
      • month = may,
      • url = {https://www.merl.com/publications/TR2020-059}
      • }
    •  Ioannidis, V., Chen, S., Giannakis, G., "Pruned Graph Scattering Transforms", International Conference on Learning Representations (ICLR), April 2020.
      BibTeX TR2020-055 PDF
      • @inproceedings{Ioannidis2020apr,
      • author = {Ioannidis, Vassilis and Chen, Siheng and Giannakis, Georgios},
      • title = {Pruned Graph Scattering Transforms},
      • booktitle = {International Conference on Learning Representations (ICLR)},
      • year = 2020,
      • month = apr,
      • url = {https://www.merl.com/publications/TR2020-055}
      • }
    •  Fehenberger, T., Millar, D.S., Koike-Akino, T., Kojima, K., Parsons, K., Griesser, H., "Huffman-coded Sphere Shaping and Distribution Matching Algorithms via Lookup Tables", IEEE Journal of Lightwave Technology, DOI: 10.1109/JLT.2020.2987210, Vol. 38, No. 10, pp. 2825 - 2833, April 2020.
      BibTeX TR2020-051 PDF
      • @article{Fehenberger2020apr2,
      • author = {Fehenberger, Tobias and Millar, David S. and Koike-Akino, Toshiaki and Kojima, Keisuke and Parsons, Kieran and Griesser, Helmut},
      • title = {Huffman-coded Sphere Shaping and Distribution Matching Algorithms via Lookup Tables},
      • journal = {IEEE Journal of Lightwave Technology},
      • year = 2020,
      • volume = 38,
      • number = 10,
      • pages = {2825 -- 2833},
      • month = apr,
      • doi = {10.1109/JLT.2020.2987210},
      • issn = {1558-2213},
      • url = {https://www.merl.com/publications/TR2020-051}
      • }
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  • Videos

  • Software Downloads