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This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert spa ...
Sound waves propagate through space and time by transference of energy between the particles in the medium, which vibrate according to the oscillation patterns of the waves. These vibrations can be captured by a microphone and translated into a digital sig ...
We present a novel implementation strategy for distributed autoregressive moving average (ARMA) graph filters. Differently from the state of the art implementation, the proposed approach has the following benefits: (i) the designed filter coefficients come ...
There are a wide variety of applications that are able to tolerate small errors in the values of the outputs, provided they are within the application-specific thresholds. For such applications, there have been many efforts to study the tradeoff involved i ...
An extensive study of digital pulse processing methods is presented. Existing methods, both traditional and more recent, are compared with original advanced techniques within an appropriate modeling and benchmarking framework. This comprehensive approach e ...
We propose a new framework, called Filtered Variation (FV), for denoising and sparse signal processing applications. These problems are inherently ill-posed. Hence, we provide regularization to overcome this challenge by using discrete time filters that ar ...
The paper presents a low power and low chip area decimation filter for a 15-bits Σ-Δ analog-to-digital converter (ADC) designed for a flywheel MEMS gyroscope. In contrary to typical solutions, in which decimation is performed after each filtering stage, in ...
Graph filters play a key role in processing the graph spectra of signals supported on the vertices of a graph. However, despite their widespread use, graph filters have been analyzed only in the deterministic setting, ignoring the impact of stochasticity i ...
Institute of Electrical and Electronics Engineers2017
Adaptive filters are at the core of many signal processing applications, ranging from acoustic noise supression to echo cancelation [1], array beamforming [2], channel equalization [3], to more recent sensor network applications in surveillance, target loc ...
Certain aspects of the present disclosure relate to a method for quantizing an analog received signal in a low-power body area network (LP-BAN) by using a limited number of quantization bits, while information of the received signal is preserved for accura ...
