Signal processing solutions are developed for biomedical problems. Image processing techniques are used to calculate the flow rate of fluids, map of DNA sequences and segment brain tumors. We are also using artificial and natural pores to build accurate analyte detection systems using sensor arrays.
Research at SenSIP spans the areas of speech/audio coding, noise cancelation and speech enhancement. Low complexity implementations of the human auditory perceptual models have been developed and efficient coding/enhancement of speech and audio are performed using these models. They are also incorporated in adaptive noise cancellation systems.
Current research in image processing involves the investigation of the use of sparse representations in image coding, denoising and compressive sensing. In addition, algorithms for 2D to 3D image transformations are also developed. Research in video processing and analysis includes the design of strategies for energy-efficient transmission, distributed coding and compressive acquisition. Furthermore, implementation aspects using multi-core DSP platforms are also considered.
Current research in Communications at the SenSIP Center are in the areas of MIMO systems, multi-carrier systems including OFDM and CDMA, and cleaned equalization coding. The following publications includes some of the by the faculty members of the SenSIP center. We have included a primer on OFDM systems.
The SenSIP Industry Consortium performs use-inspired research in sensor and information systems, adaptive and non-linear systems, digital signal and image processing, wireless communications, networks, and multimedia. Applications addressed include information processing, software systems, integrated sensing, biomedicine and genomics, defense and homeland security, sustainability and environmental technologies, speech/audio processing and telephony, imaging and video systems, low power realizations, real-time implementations, smart stages and interactive media, and vehicular sensing.
This project addresses signal processing and communication problems associated with the management of utility-scale “green” energy production. Several new signal processing, modeling, and wireless communication methods are developed for optimizing photovoltaic (PV) or solar panel arrays using sensors and other smart monitoring devices. This is a joint project with Paceco Corporation on design and implementation aspects of the sensors and smart monitoring devices.
Educational software modules for mobile devices are being developed. These are intended to be tools for students and instructors in Signal Processing and Communications courses. iPhone/iPad apps for DSP simulation are in the process of completion and related work is shown below. In addition, the SPRINT-ID system is being customized to allow lecture notes, videos and other coursework-related material to be aggregated in a single location using the Android framework.
Understanding and analyzing multimedia creation allows the development of powerful tools for musicians, designers, ecologists, and others. To work toward such tools, relevant work at the SenSIP center focuses on analyzing human activity in recordings, transforming sounds, modeling musical instruments, video summarization, activity detection and creating immersive interactive environments.
- In the News
- ISSPC 2016 Workshop
- SenSIP Industry Training and Graduate Certificate
- ITESM-SenSIP NSF Project
- SenSIP LTE System Installed at GWC
- Solar Monitoring Facility Constructed
- 2016-2021 Phase 2 I/UCRC Launched
- New NSF Project on Sensors and DSP, 2016
- SenSIP Industry Event on Big Data and Sensors
ASU SenSIP - Tech de Monterrey Workshop on Sensors, Signal Processing and Communications (SSPC). May 2016, The workshop was sponsored in part by NSF. Technical Co-sponsorship by IEEE Phoenix Chapter. Presenters included CU, GPEC, IBM Research, Lawrence Livermore Labs...
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