Pedro Julián

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—Sound localization using energy-aware hardware for sensor networks nodes is a problem with many applications in surveillance and security. In this paper, we evaluate four algorithms for sound localization using signals recorded in a natural environment with an array of commercial off-the-shelf microelectromechanical systems microphones and a specially(More)
—We propose a programmable architecture for a single instruction multiple data image processor that has its foundation on the mathematical framework of a simplicial cellular neural networks. We develop instruction primitives for basic image processing operations and show examples of processing binary and gray scale images. Fabricated in deep submicron CMOS(More)
This paper introduces a novel neural architecture which is capable of similar performance to any of the "classic" neural paradigms while having a very simple and efficient mixed-signal implementation which makes it a valuable candidate for intelligent signal processing in portable multimedia applications. The architecture and its realization circuit are(More)
— This paper describes experimental results of low power sensor nodes designed to perform bearing estimation. The nodes are intended to form a wireless sensor network able to locate an audio source. Two different nodes are tested: one is based on a Cross-correlation Derivative integrated circuit (IC), and the other on a Gradient Flow IC. Implementation(More)
We describe a low-power VLSI wake-up detector for use in an acoustic surveillance sensor network. The detection criterion is based on the degree of low-frequency periodicity in the acoustic signal. To this end, we have developed a periodicity estimation algorithm that maps particularly well to a low-power VLSI implementation. The time-domain algorithm is(More)
In this paper, we study the relationship between the standard cellular neural network (CNN) and the resonant tunneling diode (RTD)-based CNN. We investigate the functional and advanced capabilities of a new generation of CNNs that exploit the multiplicity of steady states. We also include in the analysis higher order CNNs. Furthermore, some methods for(More)