Artículos (Teoría de la Señal y Comunicaciones)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11422

Examinar

Mostrando 1 - 20 de 121

Segmentation-based lossless compression of burn wound images
(Society of Photo-optical Instrumentation Engineers, 2001) Serrano Gotarredona, María del Carmen; Acha Piñero, Begoña; Rangayyan, Rangaraj M.; Roa Romero, Laura María; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TIC203: Ingenieria Biomedica
Color images may be encoded by using a gray-scale image compression technique on each of the three color planes. Such an approach, however, does not take advantage of the correlation existing between the color planes. In this paper, a new segmentation-based lossless compression method is proposed for color images. The method exploits the correlation existing among the three color planes by treating each pixel as a vector of three components, performing region growing and difference operations using the vectors, and applying a color coordinate transformation. The method performed better than the Joint Photographic Experts Group (JPEG) standard by an average of 3.40 bits/pixel with a database including four natural color images of scenery, four images of burn wounds, and four fractal images, and it outperformed the Joint Bi-Level Image experts Group (JBIG) standard by an average of 3.01 bits/pixel. When applied to a database of 20 burn wound images, the 24 bits/pixel images were efficiently compressed to 4.79 bits/pixel, then requiring 4.16 bits/pixel less than JPEG and 5.41 bits/pixel less than JBIG.
CAD Tool for Burn Diagnosis
(Springer, 2003) Acha Piñero, Begoña; Serrano Gotarredona, María del Carmen; Acha Catalina, José Ignacio; Roa Romero, Laura María; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
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 burns: 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.
Memoria del curso de formación de profesores noveles 2002/03
(Universidad de Sevilla, 2004) Rivas Asensio, Luis Miguel; Hornillo Mellado, Susana; Cerquides Bueno, José Ramón; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
Circuit-level simulation of W-CDMA communication systems applied to the analysis of nonlinear distortion
(Wiley, 2004-11) Madero Ayora, María José; Reina Tosina, Luis Javier; Freire-Pérez, Ramón; Crespo Cadenas, Carlos; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
Different circuit-level approaches to analyze the effects of non linear distortion on coded division multiple access (CDMA) wireless communication systems are studied in order to predict spectral regro wthat the output of a nonlinear device. Measurements of a simple MESFET amplifier tested with a W-CDMA waveform are satisfactorily compared with the simulated results.
Hybrid higher-order statistics learning in multiuser detection
(Institute of Electrical and Electronics Engineers (IEEE), 2004-11) Caamano, Antonio J.; Boloix Tortosa, Rafael; Ramos, Javier; Murillo Fuentes, Juan José; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia Y Tecnología (MCYT). España; Universidad de Sevilla. TIC-155: Tratamiento de señales y comunicaciones
In this paper, we explore the significance of second- and higher-order statistics learning in communication systems. The final goal in spread-spectrum communication systems is to receive a signal of interest completely free from interference caused by other concurrent signals. To achieve this end, we exploit the structure of the interference by designing second-order statistics detectors, such as the minimum square error, in conjunction with higher-order statistics (HOS) techniques, such as the blind source separation (BSS). This hybrid higher-order statistics (HyHOS) approach enables us to alleviate BSS algorithms of one of their main problems, that is, their sensitiveness to high levels of noise. In addition, we benefit from remarkable properties of BSS in learning such as fast learning (superefficiency) and independence of the initial settings of the problem (equivariance). We successfully applied the results of this approach to the design of multiuser detectors in code-division multiple access channels. © 2004 IEEE.
Segmentation and classification of burn images by color and texture information
(Spie-soc photo-optical instrumentation engineers, 2005) Acha Piñero, Begoña; Serrano Gotarredona, María del Carmen; Acha Catalina, José Ignacio; Roa Romero, Laura María; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
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%
Blind Low Complexity Time-Of-Arrival Estimation Algorithm for UWB Signals
(Institute of Electrical and Electronics Engineers (IEEE), 2005-06) Boloix Tortosa, Rafael; Arias de Reyna Domínguez, Eva María; Murillo Fuentes, Juan José; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Educación y Ciencia (MEC). España; Junta de Andalucía; Universidad de Sevilla. TIC155: Tratamiento de Señales y Comunicaciones
This letter presents a novel time-of-arrival (TOA) blind estimation technique for ultra wideband energy detection receivers with reduced complexity. The proposed method is blind in the sense that it does not exploit any information about channel or noise power. This new approach is based on a set of approximations of the exact likelihood function (ELF) of the observed energy. Even though these approximations achieve an important reduction of complexity, the shape of the new approximated function is accurate enough compared to the ELF. Application of a threshold to the differential of the approximated log-likelihood function completes the procedure. Simulations show that the performance of the proposed method in terms of the cumulative distribution function of the estimation error approaches that of a method based on the ELF and a genie-aided algorithm with perfect knowledge of the optimal threshold.
Color-texture image segmentation based on multistep region growing
(Society of Photo-optical Instrumentation Engineers, 2006) Fondón García, Irene; Serrano Gotarredona, María del Carmen; Acha Piñero, Begoña; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
A new method for color image segmentation is proposed. It is based on a novel region-growing technique with a growth tolerance parameter that changes with step size, which depends on the variance of the actual grown region. Contrast is introduced to determine which value of the tolerance parameter is taken, choosing the one that provides the region with the highest contrast in relation to the background. Color and texture information are extracted from the image by means of a novel idea: the construction of a color distance image and a texture energy image. The color distance image is formed by calculating CIEDE2000 distance in the L*a*b* color space. The texture energy image is extracted from some statistical moments. Then, a novel texture-controlled multistep region-growing process is performed for the segmentation. One advantage of the method is that it is not designed to work with a particular kind of images. This method is tested on 80 natural color images of the Corel photo stock collection with excellent results. Numerical evidence of the quality of these results is provided by comparing them with the manual segmentation of five experts and with another color and texture segmentation algorithm
A Joint Optimization Criterion for Blind DS-CDMA Detection
(Hindawi Publishing Corporation, 2006) Durán Díaz, Iván; Cruces Álvarez, Sergio Antonio; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
This paper addresses the problem of the blind detection of a desired user in an asynchronous DS-CDMA communications system with multipath propagation channels. Starting from the inverse filter criterion introduced by Tugnait and Li in 2001, we propose to tackle the problem in the context of the blind signal extraction methods for ICA. In order to improve the performance of the detector, we present a criterion based on the joint optimization of several higher-order statistics of the outputs. An algorithm that optimizes the proposed criterion is described, and its improved performance and robustness with respect to the near-far problem are corroborated through simulations. Additionally, a simulation using measurements on a real software-radio platform at 5 GHz has also been performed.
Volterra Behavioral Model for Wideband RF Amplifiers
(IEEE, 2007-03) Crespo Cadenas, Carlos; Reina Tosina, Luis Javier; Madero Ayora, María José; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
This paper proposes a behavioral modeling approach for the description of nonlinearities in wideband wireless communication circuits with memory. The model is formally derived exploiting the dependence on frequency of the amplifier nonlinear transfer functions and reduce the number of parameters in a general Volterra-based behavioral model. To validate the proposed approach, a commercial amplifier at 915 MHz, exhibiting nonlinear memory effects, has been widely characterized using different stimuli, including two tones, quadrature phase-shift keying wideband code division multiple access, and 16-quadrature amplitude modulation signals with rectangular and root-raised cosine conforming pulses. The theoretical results have been compared with experimental data demonstrating that the model performance is comparable to the well-established memory polynomial model. Calculated and measured baseband waveforms, signal constellation, spectral regrowth and adjacent channel power ratio are tightly coincident in all cases, emphasizing the relevance of the proposed model
On Real-Time AER 2-D Convolutions Hardware for Neuromorphic Spike-Based Cortical Processing
(IEEE Computer Society, 2008) Serrano Gotarredona, Rafael; Serrano Gotarredona, María Teresa; Acosta Jiménez, Antonio José; Serrano Gotarredona, Clara; Pérez Carrasco, José Antonio; Linares Barranco, Bernabé; Linares Barranco, Alejandro; Jiménez Moreno, Gabriel; Civit Balcells, Antón; Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
In this paper, a chip that performs real-time image convolutions with programmable kernels of arbitrary shape is presented. The chip is a first experimental prototype of reduced size to validate the implemented circuits and system level techniques. The convolution processing is based on the address–event-representation (AER) technique, which is a spike-based biologically inspired image and video representation technique that favors communication bandwidth for pixels with more information. As a first test prototype, a pixel array of 16x16 has been implemented with programmable kernel size of up to 16x16. The chip has been fabricated in a standard 0.35- m complimentary metal–oxide–semiconductor (CMOS) process. The technique also allows to process larger size images by assembling 2-D arrays of such chips. Pixel operation exploits low-power mixed analog–digital circuit techniques. Because of the low currents involved (down to nanoamperes or even picoamperes), an important amount of pixel area is devoted to mismatch calibration. The rest of the chip uses digital circuit techniques, both synchronous and asynchronous. The fabricated chip has been thoroughly tested, both at the pixel level and at the system level. Specific computer interfaces have been developed for generating AER streams from conventional computers and feeding them as inputs to the convolution chip, and for grabbing AER streams coming out of the convolution chip and storing and analyzing them on computers. Extensive experimental results are provided. At the end of this paper, we provide discussions and results on scaling up the approach for larger pixel arrays and multilayer cortical AER systems.
Digital communication receivers using Gaussian processes for machine learning
(2008) Pérez Cruz, Fernando; Murillo Fuentes, Juan José
An Impedance-Based Model for the Evaluation of IM3 in Nonlinear Amplifiers Showing Memory Effects
(Wiley, 2008-03) Madero Ayora, María José; Reina Tosina, Luis Javier; Crespo Cadenas, Carlos; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
A simple model that captures nonlinear memory effects inwideband amplifiers is presented in this work. The model defines anequivalent hypothetical load impedance that explains asymmetries, inmagnitude and phase, in two-tone IM products, showing good corre-spondence with measurements. It helps to understand the intermodula-tion distortion dependence on modulation bandwidth.
Amplifier Nonlinear Modeling with RF Pulses
(IEEE, 2008-11) Crespo Cadenas, Carlos; Reina Tosina, Luis Javier; Madero Ayora, María José; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
This paper proposes a Volterra kernel identification procedure for wireless amplifiers with nonlinear memory. The technique is based on a reduced-order Volterra model for wideband amplifiers that is favorably compared with widely used memory polynomial model in terms of normalized mean square error. The identification method takes advantage of the particular model structure and is thoroughly derived with a proper selection of pulse-like waveforms of known amplitude as probing signals with special emphasis on the extraction of the fifth-order kernel. The main advantage of the method is that it allows exploring the dynamic range of the amplifier without rising the temperature in the device or altering the biasing point. For validation purposes, a commercial amplifier has been characterized and the extracted kernels have been used to predict the response under wideband code-division multiple-access-like signals. In addition to the simplicity of the deterministic approach used in this extraction procedure, the agreement of the predicted responses with measurements was highly satisfactory in all cases and permitted the capture of phenomena that are due to nonlinear memory effects.
Self-assessed Contrast-Maximizing Adaptive Region Growing
(Springer, 2009) Sánchez Mendoza, Carlos; Acha Piñero, Begoña; Serrano Gotarredona, María del Carmen; Gómez-Cía, Tomás; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
In the context of an experimental virtual-reality surgical planning software platform, we propose a fully self-assessed adaptive region growing segmentation algorithm. Our method successfully delineates main tissues relevant to head and neck reconstructive surgery, such as skin, fat, muscle/organs, and bone. We rely on a standardized and self-assessed region-based approach to deal with a great variety of imaging conditions with minimal user intervention, as only a single-seed selection stage is required. The detection of the optimal parameters is managed internally using a measure of the varying contrast of the growing regions. Validation based on synthetic images, as well as truly-delineated real CT volumes, is provided for the reader’s evaluation.
Initialization method for speech separation algorithms that work in the time-frequency domain
(Acoustical Society of America, 2010) Sarmiento Vega, María Auxiliadora; Durán Díaz, Iván; Cruces Álvarez, Sergio Antonio; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia y tecnología (España)
This article addresses the problem of the unsupervised separa tion of speech signals in realistic scenarios. An initialization procedure is proposed for independent component analysis (ICA) algorithms that work in the time-frequency domain and require the prewhitening of the observations. It is shown that the proposed method drastically reduces the permuted solu tions in that domain and helps to reduce the execution time of the algorithms. Simulations confirm these advantages for several ICA instantaneous algo rithms and the effectiveness of the proposed technique in emulated reverber ant environments.
Fast vision through frameless event-based sensing and convolutional processing: Application to texture recognition
(Institute of Electrical and Electronics Engineers, 2010) Pérez Carrasco, José Antonio; Acha Piñero, Begoña; Serrano Gotarredona, María del Carmen; Camuñas Mesa, Luis Alejandro; Serrano Gotarredona, María Teresa; Linares Barranco, Bernabé; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
Address-event representation (AER) is an emergent hardware technology which shows a high potential for providing in the near future a solid technological substrate for emulating brain-like processing structures. When used for vision, AER sensors and processors are not restricted to capturing and processing still image frames, as in commercial frame-based video technology, but sense and process visual information in a pixel-level event-based frameless manner. As a result, vision processing is practically simultaneous to vision sensing, since there is no need to wait for sensing full frames. Also, only meaningful information is sensed, communicated, and processed. Of special interest for brain-like vision processing are some already reported AER convolutional chips, which have revealed a very high computational throughput as well as the possibility of assembling large convolutional neural networks in a modular fashion. It is expected that in a near future we may witness the appearance of large scale convolutional neural networks with hundreds or thousands of individual modules. In the meantime, some research is needed to investigate how to assemble and configure such large scale convolutional networks for specific applications. In this paper, we analyze AER spiking convolutional neural networks for texture recognition hardware applications. Based on the performance figures of already available individual AER convolution chips, we emulate large scale networks using a custom made event-based behavioral simulator. We have developed a new event-based processing architecture that emulates with AER hardware Manjunath's frame-based feature recognition software algorithm, and have analyzed its performance using our behavioral simulator. Recognition rate performance is not degraded. However, regarding speed, we show that recognition can be achieved before an equivalent frame is fully sensed and transmitted.
Detección automática de vasos en retinografías
(2010) Foncubierta Rodríguez, Antonio; Serrano Gotarredona, María del Carmen; Acha Piñero, Begoña; Alemany Márquez, Pedro; Jiménez Carmona, Soledad; Fondón García, Irene; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
Principales problemas de los profesores principiantes en la enseñanza universitaria
(2010) Madero Ayora, María José; Fondón García, Irene; Sarmiento Vega, María Auxiliadora
Se presentan y discuten algunas reflexiones sobre los principales problemas que los profesores principiantes encuentran en la enseñanza universitaria. Dichas dificultades se clasifican y analizan en tres ámbitos: el de la enseñanza, el de las relaciones interpersonales y el de la gestión o el contexto institucional. Se resalta la importancia de una adecuada formación pedagógica por parte del docente novel y el papel de la acción tutorial. Se revisa también los retos que suponen para el profesor principiante la actual reforma del modelo universitario español en el marco del Espacio Europeo de Educación Superior y el conflicto investigación-docencia. Esto porque la actividad investigadora no sólo es indispensable para la continua evolución científica del profesor universitario, sino que también depende de ella su continuidad en la carrera docente. Dicha actividad es a menudo difícil de compatibilizar con la puramente docente, especialmente para el docente principiante.
Strict separability and identifiability of a class of ICA models
(2010-03) Murillo Fuentes, Juan José; Boloix Tortosa, Rafael; Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TIC-155: Tratamiento de señales y comunicaciones
In this letter we focus on the application of independent component analysis (ICA) to a class of overdetermined blind source separation (BSS) problems. The mixing matrix in the BSS model is the product of an unknown square diagonal matrix and a projection matrix. The last matrix performs a known projection to the same or larger dimensional space. We demonstrate the conditions for the model to be strictly separable and identifiable under the statistical independence condition, paying attention to permutations and relative scalings. These results find application, e.g., in the channel estimation of ZP-OFDM and Precoded-OFDM systems

Examinar

Examinando Artículos (Teoría de la Señal y Comunicaciones) por Fecha de publicación