iTEAM

Home Research Research Areas Signal Processing

Signal Processing

Digital processing of signals applied to: image, sound, communications, sensor data and biological data. Industrial and financial applications.

Research Topics

Underwater Acoustics

We employ Passive Acoustic Monitoring techniques to advance in the study of marine mammals and anthropogenic sounds. This is achieved by developing new acoustic instrumentation and signal processing algorithms to detect and characterise underwater acoustic events. Our goal is to improve the understanding of how anthropogenic sounds impacts on the marine biodiversity as well as to study the population abundance, seasonality and behaviour of marine mammals.

High performance arithmetic and DSP operators for FPGA

Design of arithmetic operators and digital signal processing kernels optimized for their implementation in Altera and Xilinx FPGA devices.

FPGA-based DSP for ultrasound waves

Ultrasounds are used in non-destructive measurements in nuclear and aeronautic sectors. This line is focused in the design of digital signal processing algorithms for ultrasound waves and their hardware architectures for FPGA devices: FIR and IIR filters, multirate filters, pipeline-interleaved filters, envelope detectors, logarithmic converters,interpolators for Giga-sample operation, beanforming for array sensors. This R&D line is developed for the company TECNATOM under the contract “Desarrolllos de tecnologías electrónicas”.

Algorithms and architectures for FPGA-based software radios

Algorithms and architectures for FPGA-based software radios Algorithms and architectures to implement digital communication systems in FPGA devices: re-sampling for transmission, digital up & down conversion, synchronization for QAM systems, synchronization for OFDM systems, digitally implemented analog modulations. Three FPGA-based demonstrators have been developed: 10 Mbps digital IF QPSK MODEM, 54 Mbps base-band OFDM MODEM and fully digital FM receiver.

Algorithms and architectures for advanced Forward Error Correction (FEC)

The objective of this research is the development of algorithms and architectures for hardware implementation of FEC blocks that will be required in future communications systems. We have focused in: Binary Low-Density Parity-Check codes decoders, Non-binary Low-Density Parity-Check codes decoders and Soft decoding of Reed-Solomon codes. We want to improve the operation of the LDPC decoders for high SNRs where the error-floor can appears. We have developed an FPGA-based hardware LDPC emulator to accelerate simulations for very low bit rates.

Signal Processing for Audio Applications

There are multiple audio applications that benefit from signal processing algorithms. Some examples we have expertise on are:

- Spatial directionality of arrays of microphones / loudspeakers. 
- Spatial audiometry using synthesized spatial sounds by software. 
- Evaluation of the perceived annoyance of a sound and the relation to its objective characteristics in order to improve its subjective perception.

Efficient Implementation of Algorithms in Multicore and Manycore Devices

When considering multiple microphones, rate frequencies of 44100 samples/second/input, and a high computational burden due to complex algorithms, efficient software implementation shows to be crucial. Research on how multicore and manycore (GPUs) devices can be used for task parallelization is an open and very promising issue.

Distributed and Collaborative Sound Signal Processing

Different sound applications interact with the environment using one or more transducers but centralizing their associated signal processing. Advances made in the field of distributed computing, together with the availability of the necessary hardware and software, have allowed for the development of powerful sound signal processing systems whose interaction with the environment involves multitude of transducers sets. Applications: Different sound environments in a single space, Human-machine interfaces based on sounds, Seamless mobile sound spaces.

Adaptive Filtering

Adaptive filters are basic in multitude of fields such control, aerospace, communications, automotive, etc. Linear and non-linear filters can be used including a wide variety of adaptive algorithms as LMS, RLS, AP, ... and combinations of them. Applications: Room compensation, active noise control, Noise identification.

Active Noise Control

Low- frequency noise levels can be reduced if a counter-phase wave is added at the listener location. When noise has to be cancelled at multiple listening points, multichannel systems are needed to generate the proper signals. Consequently, advanced signal processing algorithms have to be carefully designed to assure listeners perceive a lower and, possibly, less annoying noise. Applications: Car engine noise, airplane, car and train interior noises.


Contact:

Instituto de Telecomunicaciones
y Aplicaciones Multimedia (iTEAM)

Edificio 8G. Planta 4ª, acceso D
Universitat Poltècnica de València
Camino de Vera, s/n
46022 Valencia
SPAIN

Email info@iteam.upv.es

Phone +34 963879580

Fax +34 963879583

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