José I. Acha

Computational structures for fast implementation of L-path and L-block digital filters

One of the major problems in the multi-DSP (digital signal processor) implementation of L-path and L-block digital filters is the hardware complexity-throughput rate tradeoff. The author presents computational structures based on the theory of fast algorithms for short linear convolutions, which are suitable for the implementation of these types of digital filters. He also compares the performance of the structures with two previously published ones. The comparison shows that the schemes proposed here are faster and that the complexity-throughput tradeoffs can easily be controlled by the designer. >

Design of General Voltage- or Current-Controlled Resistive Elements and their Applications to the Synthesis of Nonlinear Networks

New structures are proposed for the realization of voltage- or current-controlled resistors and conductors. The new devices have improved sensitivity parameters if compared with previously reported modules. Also an original contribution is the design of ungrounded elements which enlarge the usefulness of these structures. Applications of these elements to the synthesis of resistive nonlinear networks are studied. Experimental realizations are given and are in agreement with the theoretid results.

Segmentation and classification of burn images by color and texture information

In this paper, a burn color image segmentation and classification system is proposed. The aim of the system is to separate burn wounds from healthy skin, and to distinguish among the different types of burns (burn depths). Digital color photographs are used as inputs to the system. The system is based on color and texture information, since these are the characteristics observed by physicians in order to form a diagnosis. A perceptually uniform color space (L*u*v*) was used, since Euclidean distances calculated in this space correspond to perceptual color differences. After the burn is segmented, a set of color and texture features is calculated that serves as the input to a Fuzzy-ARTMAP neural network. The neural network classifies burns into three types of burn depths: superficial dermal, deep dermal, and full thickness. Clinical effectiveness of the method was demonstrated on 62 clinical burn wound images, yielding an average classification success rate of 82%.

Self-Synchronization of Asynchronous Sequential Circuits Employing a General Clock Function

A self-synchronization model is developed. It is based on a general clock function which depends only on the state variables. This function is associated with the flip-flop type to be used and is independent of the flow table. A modular implementation which uses integrated circuits is obtained. With this technique, the synthesis procedures for synchronous machines can be directly applicable to asynchronous circuits without taking care of the critical races and essential hazards.

Eigendecomposition of self-tuned cumulant-matrices for blind source separation

Existing algorithms for blind source separation are often based on the eigendecomposition of fourth-order cumulant matrices. However, when the cumulant matrices have close eigenvalues, their eigenvectors are very sensitive to errors in the estimation of the matrices.In this paper, we show how to produce a cumulant matrix that has a well-separated extremal eigenvalue. The corresponding eigenvector is thus well conditioned and can be used to develop robust algorithms for blind source extraction. Some numerical experiments are provided to illustrate the effectiveness of the proposed approach.

CAD tool for burn diagnosis.

In this paper a new system for burn diagnosis is proposed. The aim of the system is to separate burn wounds from healthy skin, and the different types of burns (burn depths) from each other, identifying each one. The system is based on the colour and texture information, as these are the characteristics observed by physicians in order to give a diagnosis. We use a perceptually uniform colour space (L*u*v*), since Euclidean distances calculated in this space correspond to perceptually colour differences. After the burn is segmented, some colour and texture descriptors are calculated and they are the inputs to a Fuzzy-ARTMAP neural network. The neural network classifies them into three types of bums: superficial dermal, deep dermal and full thickness. Clinical effectiveness of the method was demonstrated on 62 clinical burn wound images obtained from digital colour photographs, yielding an average classification success rate of 82% compared to expert classified images.

Application of Independent Component Analysis to Edge Detection and Watermarking

It has been shown that a typical Independent Component Analysis (ICA) of an image provides a good estimation for the responses of the neurons of the visual cortex and their patterns of excitation. In this paper we apply ICA to obtain a decomposition of the image into a set of basis or features. These particular features can be used to develop a new algorithm for detecting the edges of the image. The performance of the proposed approach is demonstrated experimentally.

Segmentation of burn images based on color and texture information

In this paper a color image segmentation algorithm for its application to burn wound images is proposed. It takes into accoutn both color and texture information to perform the segmentation. We used the perceptually uniform CIE L*u*v* color space. Texture information is considered by extracting a small trimming from the part to be segmented. Then this mask is slid along the image and a transformed image is calculated, where each pixel is the sum of Euclidean distances in the L*u*v* color coordinates between all the color values in the mask and the pixels under it. Afterwards the transformed image must be thresholded to obtain the segmented image. The threshold is automatically determined by a modification of Otsus method. We have tested the algorithm with 30 images, obtaining very good results in most of them.

A Conjugate Gradient Method and Simulated Annealing for Blind Separation of Sources

This paper presents a new procedure for Blind Separtion of non-Gaussian Sources. It is proven that the estimation of the separating system can be based on the cancellation of some second partial derivatives of the output cross-cumulants. The resulting method is based on a conjutate gradient algorithm on the Stiefel manifold. Simulated annealing is used to obtain a good initial value and improve the rate of convergence.

Study and modeling of noise on the low voltage part of the electrical power distribution network between 30 kHz and 1 MHz

In this paper, an extensive set of noise measurements on the low voltage part of the electrical power distribution network is presented. These measurements were taken in a laboratory environment for several months by means of a spectrum analyzer. Automatic remote measurement software was specifically designed and used for this purpose. The frequencies considered range from 30 kHz to 1 MHz, well above the allowed band specified in the European standard to communications over the electrical power distribution network. These noise measurements are important for the design of communication systems, such as power line carrier, which use the distribution line as a communications medium. Several kinds of noise are specifically studied, including impulsive noise, switching and non-switching periodic noise and background noise. In particular, the behavior of noise levels as a function of time of day is analyzed. Finally, a statistical model is also shown.