The undersampled wireless acoustic sensor network scenario: some preliminary results and open research issues

Advances in hardware technology pave the way to small, low power wireless sensor devices, such as wireless microphones. This makes it possible to use a large number, i.e. thousands, of microphones at positions where it is not feasible to put wired microphones, creating an enormous potential for improved flexibility and performance within a transparent acoustic communication context. In order to reduce battery consumption, each of the wireless microphones has to be sampled much below the Nyquist sample rate. In this paper we will discuss some preliminary results and open research issues that are involved in such an Undersampled Wireless Acoustic Sensor (UWAS) network scenario

Equal convergence conditions for normal- and partitioned-frequency domain adaptive filters

\u3cp\u3eConvergence characteristics of adaptive filters are influenced by statistical properties of the input signal. In order to remove this dependency, decorrelation can be applied with a frequency- domain adaptive filter (FDAF), in which the length M of the transformation between the time and the frequency domain is chosen to be equal to the length N of the adaptive filter. The relevant length M is determined by the statistical properties of the input signal and needs not to be equal to N. Both lengths M and N can be decoupled by using partitioned frequency-domain adaptive filters (PFDAFs). Statistical conditions are derived for the input signal in such a way that both PFDAF and FDAF have equal convergence properties.\u3c/p\u3

Adaptive blind signal separation using a new simplified mixing model

This paper addresses the problem of separating multiple speakers from mixtures of these that are obtained using multiple microphones in a room. A new adaptive blind separation algorithm is proposed which is based on a new simplified mixing model and uses only second order statistics. The simplified model uses the fact that the acoustic transfer functions from a single source to two closely spaced microphones are very similar. Under certain conditions one acoustic transfer function and a di#erence, which is made up of a timedelay and an attenuation factor in this paper, will be enough. Simulation results using real speech mixtures recorded in a normal living room show the e#ectiveness of this algorithm. Keywords---adaptive filtering; blind signal separation; second order statistics I. Introduction Blind Signal Separation (BSS), with the framework of independent component analysis, deals with the problem of separating independent sources given only mixtures of those sources while both..

A new blind signal separation algorithm based on second-order statistics

This paper addresses the problem of separating multiple speakers from mixtures of these that are obtained using multiple microphones in a room. A new adaptive blind signal separation algorithm is derived which is entirely based on Second Order Statistics which is entitled CoBliSS. The CoBliSS algorithm can run in offline or online (adaptive) mode. One of the advantages of the CoBliSS algorithm is that no assumptions are made about the probability density functions or other properties of the signals. Experiments with real recordings were carried out in a normal living room which show that the algorithm has good performance. As opposed to most other algorithms no parameters need to be tuned

An analysis of real-Fourier domain based adaptive algorithms implemented with the Hartley transform using cosine-sine symmetries

The least mean squared (LMS) algorithm and its variants have been the most often used algorithms in adaptive signal processing. However the LMS algorithm suffers from a high computational complexity, especially with large filter lengths. The Fourier transform-based block normalized LMS (FBNLMS) reduces the computation count by using the discrete Fourier transform (DFT) and exploiting the fast algorithms for implementing the DFT. Even though the savings achieved with the FBNLMS over the direct-LMS implementation are significant, the computational requirements of FBNLMS are still very high, rendering many real-time applications, like audio and video estimation, infeasible. The Hartley transform-based BNLMS (HBNLMS) is found to have a computational complexity much less than, and a memory requirement almost of the same order as, that of the FBNLMS. This paper is based on the cosine and sine symmetric implementation of the discrete Hartley transform (DHT), which is the key in reducing the computational complexity of the FBNLMS by 33% asymptotically (with respect to multiplications). The parallel implementation of the discrete cosine transform (DCT) in turn can lead to more efficient implementations of the HBNLMS

Complexity of pruning strategies for the frequency domain LMS algorithm

Large adaptive filters are frequently used in diverse applications such as channel equalization, interference suppression, beamforming, etc. The least mean squared (LMS) algorithm and its variants form one of the basic building blocks of adaptive systems. The frequency domain implementations of the LMS algorithm are preferred in practice since the computational burden of LMS can be reduced significantly by using the vast family of fast fourier transform (FFT) algorithms. Despite the advantage of frequency domain LMS over regular-LMS, the increasing computational complexity of the FFT-based LMS algorithms (with filter length) makes them unattractive for applications with a large number of filter taps. In this paper, FFT pruning is used to reduce the computational cost of frequency domain LMS by exploiting the structure of the LMS algorithm. We study various pruning strategies with our objective being reduction in computational burden and conclude that transform decomposition is the most appropriate pruning strategy. Using this pruning technique, worst-case computational savings of 10% and 5% can be achieved for applications that use filter lengths on the order of a few hundreds and a few thousands, respectively. In delay-sensitive applications, substantially more savings can be effected by pruning

Efficient realization of the block frequency domain adaptive filter

In many frequency domain adaptive lters Fast Fourier Fourier Transforms FFTs are used to transform signals which are augmented with zeros The overall computational complexity of these adaptive lters is mainly determined by these windowed FFTs rather than by the ltering operation itself This contribution presents a new way of calculating these windowed FFTs efficiently In addition a method is deduced for implementing nonwindowed FFTs of overlapping input data using the previously mentioned ecient windowed FFTs Also a method is presented for implementing the windowed FFTs in the update part even more efficient

Mujeres transgresoras: formación política y organizativa frente a la violencia sexual contra las mujeres en los Montes de María

El presente artículo indaga sobre la violencia sexual hacia las mujeres como arma de guerra en el marco del conflicto armado colombiano. Toma como referencia el caso de la región de los Montes de María y enfatiza en los repertorios de acción del paramilitarismo en la zona. Da cuenta de cómo el control de la vida, del cuerpo y del pensamiento de las mujeres, así como la transgresión de las prácticas de la vida cotidiana han sido instrumentos utilizados por el paramilitarismo para generar un total dominio territorial, de tal manera que el cuerpo de las mujeres ha sido catalogado como botín de guerra. Además, analiza la transgresión como práctica política desde el ámbito del feminismo, entendida como las transformaciones y resistencias que hacen las mujeres a las prácticas de la cultura patriarcal que las subordina y violenta.This article explores sexual violence against women as a weapon of war in the context of the colombian armed conflict, particularly in the region of Montes de Maria, emphasizing on paramilitary violent repertoires. Control of women’s life, body and mind and the transgression of everyday life practices have been used as tools by paramilitarism to generate total territorial control. As a consequence, the bodies of women have been listed as spoils of war. Furthermore, transgression is analyzed as a political practice from a feminist perspective, understood as transformations and resistance against patriarchal culture that subordinates and abused wome