Daily and seasonal thermal stresses in tilings: a field survey combined with numeric modeling

This study investigates thermally induced tensile stresses in ceramic tilings. Daily and seasonal thermal cycles, as well as, rare but extreme events, such as a hail-storm striking a heated terrace tiling, were studied in the field and by numerical modeling investigations. The field surveys delivered temperature– time diagrams and temperature profiles across tiling systems. These data were taken as input parameters for modeling the stress distribution in the tiling system in order to detect potential sites for material failure. Dependent on the thermal scenario (e.g., slow heating of the entire structure during morning and afternoon, or a rapid cooling of the tiles by a rain storm) the modeling indicates specific locations with high tensile stresses. Typically regions along the rim of the tiling field showed stresses, which can become critical with respect to the adhesion strength. Over the years, ongoing cycles of thermal expansion–contraction result in material fatigue promoting the propagation of cracks. However, the installation of flexible waterproofing membranes (applied between substrate and tile adhesive) represents an efficient technical innovation to reduce such crack propagation as confirmed by both numerical modeling results and microstructural studies on real systems.

The Distribution of the Irreducibles in an Algebraic Number Field

The objective of this thesis is to study the distribution of the number of principal ideals generated by an irreducible element in an algebraic number field, namely in the non-unique factorization ring of integers of such a field. In particular we are investigating the size of M(x), defined as M ( x ) =∑ (α) α irred.|N (α)|≤≠ 1, where x is any positive real number and N (α) is the norm of α. We finally obtain asymptotic results for hl(x).

INCREASED EXPRESSION OF ONE OF TWO ADENOSINE DEAMINASE ALLELES IN A HUMAN CHORIOCARCINOMA CELL LINE FOLLOWING SELECTION WITH ADENINE NUCLEOSIDES

The human choriocarcinoma cell line JEG-3 is heterozygous at the adenosine deaminase (ADA) gene locus. Both allelic genes are under strong but incomplete repression causing a very low level expression of the gene locus. Because cytotoxic adenosine analogues such as 9-(beta)-D arabinofuranosyladenine (ara-A) and 9-(beta)-D xylofuranosyladenine (xyl-A) can be specifically detoxified by the action of ADA, these analogues were used to select for JEG-3 derived cells which had increased ADA expression. When JEG-3 cells were subjected to a multi-step, successively increasing dosage of either ara-A or xyl-A, resistant cells with increased ADA expression were generated. This increased ADA expression in the resistant cells was unstable, so that when the selective pressure was removed, cellular ADA expression would decrease. Subclone analysis of xyl-A resistant cells revealed that compared to parental JEG-3 cells, individual resistant cells had either elevated ADA levels or decreased adenosine kinase (ADK) levels or both. This altered ADA and ADK expression in the resistant cells were found to be independent events. Because of high endogenous tissue conversion factor (TCF) expression in the JEG-3 cells, the allelic nature of the increased ADA expression in most of the resistant cells could not be determined. However, several resistant subcloned cells were found to have lost TCF expression. These TCF('-) cells expressed only the ADA*2 allelic gene product. Cell fusion experiments demonstrated that the ADA*1 allelic gene was intact and functional in the A3-1A7 cell line. Chromosomal analysis of the A3-1A7 cells showed that they had no double-minutes or homogeneously staining chromosomal regions, although a pair of new chromosomes were found in these cells. Segregation analysis of the hybrid cells indicated that an ADA*2 allelic gene was probably located on this new chromosome. The analysis of the A3-1A7 cell line suggested that the expression of only ADA 2 in these cells was the result of possibly a cis-deregulation of the ADA gene locus or more probably an amplification of the ADA*2 allelic gene. Two effective positive selection systems for ADA('+) cells were also developed and tested. These selection systems should eventually lead to the isolation of the ADA gene.^

IDRA (IDeal Resource Allocation): Computing ideal speedups in parallel logic programming

We present a technique to estimate accurate speedups for parallel logic programs with relative independence from characteristics of a given implementation or underlying parallel hardware. The proposed technique is based on gathering accurate data describing one execution at run-time, which is fed to a simulator. Alternative schedulings are then simulated and estimates computed for the corresponding speedups. A tool implementing the aforementioned techniques is presented, and its predictions are compared to the performance of real systems, showing good correlation.

Collective Organization of Complex Networks: Emergent Scales, Vulnerability, and Targeting of Desired Dynamics

Cuando una colectividad de sistemas dinámicos acoplados mediante una estructura irregular de interacciones evoluciona, se observan dinámicas de gran complejidad y fenómenos emergentes imposibles de predecir a partir de las propiedades de los sistemas individuales. El objetivo principal de esta tesis es precisamente avanzar en nuestra comprensión de la relación existente entre la topología de interacciones y las dinámicas colectivas que una red compleja es capaz de mantener. Siendo este un tema amplio que se puede abordar desde distintos puntos de vista, en esta tesis se han estudiado tres problemas importantes dentro del mismo que están relacionados entre sí. Por un lado, en numerosos sistemas naturales y artificiales que se pueden describir mediante una red compleja la topología no es estática, sino que depende de la dinámica que se desarrolla en la red: un ejemplo son las redes de neuronas del cerebro. En estas redes adaptativas la propia topología emerge como consecuencia de una autoorganización del sistema. Para conocer mejor cómo pueden emerger espontáneamente las propiedades comúnmente observadas en redes reales, hemos estudiado el comportamiento de sistemas que evolucionan según reglas adaptativas locales con base empírica. Nuestros resultados numéricos y analíticos muestran que la autoorganización del sistema da lugar a dos de las propiedades más universales de las redes complejas: a escala mesoscópica, la aparición de una estructura de comunidades, y, a escala macroscópica, la existencia de una ley de potencias en la distribución de las interacciones en la red. El hecho de que estas propiedades aparecen en dos modelos con leyes de evolución cuantitativamente distintas que siguen unos mismos principios adaptativos sugiere que estamos ante un fenómeno que puede ser muy general, y estar en el origen de estas propiedades en sistemas reales. En segundo lugar, proponemos una medida que permite clasificar los elementos de una red compleja en función de su relevancia para el mantenimiento de dinámicas colectivas. En concreto, estudiamos la vulnerabilidad de los distintos elementos de una red frente a perturbaciones o grandes fluctuaciones, entendida como una medida del impacto que estos acontecimientos externos tienen en la interrupción de una dinámica colectiva. Los resultados que se obtienen indican que la vulnerabilidad dinámica es sobre todo dependiente de propiedades locales, por tanto nuestras conclusiones abarcan diferentes topologías, y muestran la existencia de una dependencia no trivial entre la vulnerabilidad y la conectividad de los elementos de una red. Finalmente, proponemos una estrategia de imposición de una dinámica objetivo genérica en una red dada e investigamos su validez en redes con diversas topologías que mantienen regímenes dinámicos turbulentos. Se obtiene como resultado que las redes heterogéneas (y la amplia mayora de las redes reales estudiadas lo son) son las más adecuadas para nuestra estrategia de targeting de dinámicas deseadas, siendo la estrategia muy efectiva incluso en caso de disponer de un conocimiento muy imperfecto de la topología de la red. Aparte de la relevancia teórica para la comprensión de fenómenos colectivos en sistemas complejos, los métodos y resultados propuestos podrán dar lugar a aplicaciones en sistemas experimentales y tecnológicos, como por ejemplo los sistemas neuronales in vitro, el sistema nervioso central (en el estudio de actividades síncronas de carácter patológico), las redes eléctricas o los sistemas de comunicaciones. ABSTRACT The time evolution of an ensemble of dynamical systems coupled through an irregular interaction scheme gives rise to dynamics of great of complexity and emergent phenomena that cannot be predicted from the properties of the individual systems. The main objective of this thesis is precisely to increase our understanding of the interplay between the interaction topology and the collective dynamics that a complex network can support. This is a very broad subject, so in this thesis we will limit ourselves to the study of three relevant problems that have strong connections among them. First, it is a well-known fact that in many natural and manmade systems that can be represented as complex networks the topology is not static; rather, it depends on the dynamics taking place on the network (as it happens, for instance, in the neuronal networks in the brain). In these adaptive networks the topology itself emerges from the self-organization in the system. To better understand how the properties that are commonly observed in real networks spontaneously emerge, we have studied the behavior of systems that evolve according to local adaptive rules that are empirically motivated. Our numerical and analytical results show that self-organization brings about two of the most universally found properties in complex networks: at the mesoscopic scale, the appearance of a community structure, and, at the macroscopic scale, the existence of a power law in the weight distribution of the network interactions. The fact that these properties show up in two models with quantitatively different mechanisms that follow the same general adaptive principles suggests that our results may be generalized to other systems as well, and they may be behind the origin of these properties in some real systems. We also propose a new measure that provides a ranking of the elements in a network in terms of their relevance for the maintenance of collective dynamics. Specifically, we study the vulnerability of the elements under perturbations or large fluctuations, interpreted as a measure of the impact these external events have on the disruption of collective motion. Our results suggest that the dynamic vulnerability measure depends largely on local properties (our conclusions thus being valid for different topologies) and they show a non-trivial dependence of the vulnerability on the connectivity of the network elements. Finally, we propose a strategy for the imposition of generic goal dynamics on a given network, and we explore its performance in networks with different topologies that support turbulent dynamical regimes. It turns out that heterogeneous networks (and most real networks that have been studied belong in this category) are the most suitable for our strategy for the targeting of desired dynamics, the strategy being very effective even when the knowledge on the network topology is far from accurate. Aside from their theoretical relevance for the understanding of collective phenomena in complex systems, the methods and results here discussed might lead to applications in experimental and technological systems, such as in vitro neuronal systems, the central nervous system (where pathological synchronous activity sometimes occurs), communication systems or power grids.

Propiedades de materiales mediante análisis de radiación aleatoria

Las técnicas de speckle tienen un gran interés científico e ingenieril, ya que son métodos de ejecución rápida y no destructiva, con base en el análisis de las fluctuaciones de intensidad de la radiación producida cuando la luz coherente de un haz láser es esparcida por un material dado. En este caso se produce un patrón aleatorio de interferencia y difracción donde la suma de las componentes desfasadas dará lugar a máximos y mínimos de intensidad en distintos puntos del espacio. Éste, pese a tratarse de un ruido nocivo en multitud de áreas tales como la transmisión de señales o la holografía, tiene importantes propiedades físicas que lo caracterizan y lo hacen útil como medio para analizar sistemas reales de muy diversa índole. En el presente estudio, se ha llevado a cabo un análisis polarimétrico de la radiación aleatoria esparcida por una serie de muestras metálicas y dieléctricas con el objetivo de establecer una base comparativa que nos permita poder distinguir unas de otras. Para este fin se han comparado los parámetros de polarización de Stokes, el grado de polarización de la luz, las distribuciones de intensidad y el tamaño medio del speckle registrado en los distintos patrones de intensidad. Además, se analizará la dependencia de la rugosidad en el grado de polarización de la luz para los distintos medios sometidos a estudio. Abstract Speckle techniques have a great scientific and engineering interest as they are methods of rapid and non-destructive execution, based on the analysis of the fluctuations of intensity of the radiation produced when coherent light of a laser beam is scattered by a material given. In this case, a random pattern of interference and diffraction occurs where the sum of phase shifted components will result in maximum or minimum of intensity at different points in space. This, despite being a harmful noise in many areas such as signal transmission or holography, has important physical properties that characterize it and make it useful as a means to analyze real systems of various kinds. In the present study, we have conducted a polarimetric analysis of the random radiation scattered by a series of metal and dielectric samples in order to establish a comparative basis to allow us to distinguish one from another. To this end we have compared, the stokes polarization parameters, the degree of polarization (DOP), the intensity distributions and the average size of the speckle registered in the different intensity patterns. Furthermore, dependence of roughness in the DOP of light for the different means under study will be analyzed.

Educational Project for the Teaching of Control of Electric Traction Drives

Electric vehicles constitute a multidisciplinary subject that involves disciplines such as automotive, mechanical, electrical and control engineering. Due to this multidisciplinary technical nature, practical teaching methodologies are of special relevance. Paradoxically, in the past, the training of engineers specializing in this area has lacked the practical component represented by field tests, due to the difficulty of accessing real systems. This paper presents an educational project specifically designed for the teaching and training of engineering students with different backgrounds and experience. The teaching methodology focuses on the topology of electric traction drives and their control. It includes two stages, a simulation computer model and a scaled laboratory workbench that comprises a traction electrical drive coupled to a vehicle emulator. With this equipment, the effectiveness of different traction control strategies can be analyzed from the point of view of energy efficiency, robustness, easiness of implementation and acoustic noise.

Plataformas experimentales para la formación en el área de la electrónica en entornos de e-learning

El campo de estudio relacionado con los laboratorios remotos en el ámbito educativo de las ciencias y la ingeniería está sufriendo una notable expansión ante la necesidad de adaptar los procesos de aprendizaje en dichas áreas a las características y posibilidades de la formación online. Muchos de los recursos educativos basados en esta tecnología, existentes en la actualidad, presentan ciertas limitaciones que impiden alcanzar las competencias que se deben adquirir en los laboratorios de ingeniería. Estas limitaciones están relacionadas con diferentes aspectos de carácter técnico y formativo. A nivel técnico las limitaciones principales se centran en el grado de versatilidad que son capaces de proporcionar comparado con el que se dispone en un laboratorio tradicional y en el modo de interacción del usuario, que provoca que el estudiante no distinga claramente si está realizando acciones sobre sistemas reales o simulaciones. A nivel formativo las limitaciones detectadas son relevantes para poder alcanzar un aprendizaje significativo. En concreto están relacionadas principalmente con un escaso sentimiento de inmersión, una reducida sensación de realismo respecto a las operaciones que se realizan o la limitada posibilidad de realizar actividades de forma colaborativa. La aparición de nuevas tecnologías basadas en entornos inmersivos, unida a los avances producidos relacionados con el aumento de la capacidad gráfica de los ordenadores y del ancho de banda de acceso a Internet, han hecho factible que las limitaciones comentadas anteriormente puedan ser superadas gracias al desarrollo de nuevos recursos de aprendizaje surgidos de la fusión de laboratorios remotos y mundos virtuales 3D. Esta tesis doctoral aborda un trabajo de investigación centrado en proponer un modelo de plataformas experimentales, basado en la fusión de las dos tecnologías mencionadas, que permita generar recursos educativos online que faciliten la adquisición de competencias prácticas similares a las que se consiguen en un laboratorio tradicional vinculado a la enseñanza de la electrónica. El campo de aplicación en el que se ha focalizado el trabajo realizado se ha centrado en el área de la electrónica aunque los resultados de la investigación realizada se podrían adaptar fácilmente a otras disciplinas de la ingeniería. Fruto del trabajo realizado en esta tesis es el desarrollo de la plataforma eLab3D, basada en el modelo de plataformas experimentales propuesto, y la realización de dos estudios empíricos llevados a cabo con estudiantes de grado en ingeniería, muy demandados por la comunidad investigadora. Por un lado, la plataforma eLab3D, que permite llevar a cabo de forma remota actividades prácticas relacionadas con el diseño, montaje y prueba de circuitos electrónicos analógicos, aporta como novedad un dispositivo hardware basado en un sistema de conmutación distribuido. Dicho sistema proporciona un nivel de versatilidad muy elevado, a nivel de configuración de circuitos y selección de puntos de medida, que hace posible la realización de acciones similares a las que se llevan a cabo en los laboratorios presenciales. Por otra parte, los estudios empíricos realizados, que comparaban la eficacia educativa de una metodología de aprendizaje online, basada en el uso de la plataforma eLab3D, con la conseguida siguiendo una metodología clásica en los laboratorios tradicionales, mostraron que no se detectaron diferencias significativas en el grado de adquisición de los resultados de aprendizaje entre los estudiantes que utilizaron la plataforma eLab3D y los que asistieron a los laboratorios presenciales. Por último, hay que destacar dos aspectos relevantes relacionados directamente con esta tesis. En primer lugar, los resultados obtenidos en las experiencias educativas llevadas a cabo junto a valoraciones obtenidas por el profesorado que ha colaborado en las mismas han sido decisivos para que la plataforma eLab3D se haya integrado como recurso complementario de aprendizaje en titulaciones de grado de ingeniería de la Universidad Politécnica de Madrid. En segundo lugar, el modelo de plataformas experimentales que se ha propuesto en esta tesis, analizado por investigadores vinculados a proyectos en el ámbito de la fusión nuclear, ha sido tomado como referencia para generar nuevas herramientas de formación en dicho campo. ABSTRACT The field of study of remote laboratories in sciences and engineering educational disciplines is undergoing a remarkable expansion given the need to adapt the learning processes in the aforementioned areas to the characteristics and possibilities of online education. Several of the current educational resources based on this technology have certain limitations that prevent from reaching the required competencies in engineering laboratories. These limitations are related to different aspects of technical and educational nature. At the technical level, they are centered on the degree of versatility they are able to provide compared to a traditional laboratory and in the way the user interacts with them, which causes the student to not clearly distinguish if actions are being performed over real systems or over simulations. At the educational level, the detected limitations are relevant in order to reach a meaningful learning. In particular, they are mainly related to a scarce immersion feeling, a reduced realism sense regarding the operations performed or the limited possibility to carry out activities in a collaborative way. The appearance of new technologies based on immersive environments, together with the advances in graphical computer capabilities and Internet bandwidth access, have made the previous limitations feasible to be overcome thanks to the development of new learning resources that arise from merging remote laboratories and 3D virtual worlds. This PhD thesis tackles a research work focused on the proposal of an experimental platform model, based on the fusion of both mentioned technologies, which allows for generating online educational resources that facilitate the acquisition of practical competencies similar to those obtained in a traditional electronics laboratory. The application field, in which this work is focused, is electronics, although the research results could be easily adapted to other engineering disciplines. A result of this work is the development of eLab3D platform, based on the experimental platform model proposed, and the realization of two empirical studies with undergraduate students, highly demanded by research community. On one side, eLab3D platform, which allows to accomplish remote practical activities related to the design, assembling and test of analog electronic circuits, provides, as an original contribution, a hardware device based on a distributed switching system. This system offers a high level of versatility, both at the circuit configuration level and at the selection of measurement points, which allows for doing similar actions to those conducted in hands-on laboratories. On the other side, the empirical studies carried out, which compare the educational efficiency of an online learning methodology based on the use of eLab3D platform with that obtained following a classical methodology in traditional laboratories, shows that no significant differences in the acquired degree of learning outcomes among the students that used eLab3D platform and those that attended hands-on laboratories were detected. Finally, it is important to highlight two relevant aspects directly related with this thesis work. First of all, the results obtained in the educational experiences conducted, along with the assessment from the faculty that has collaborated in them, have been decisive to integrate eLab3D platform as a supplementary learning resource in engineering degrees at Universidad Politecnica de Madrid. Secondly, the experimental platform model originally proposed in this thesis, which has been analysed by nuclear fusion researchers, has been taken as a reference to generate new educational tools in that field.

Systematic derivation of partition functions for ligand binding to two-dimensional lattices

The Ising problem consists in finding the analytical solution of the partition function of a lattice once the interaction geometry among its elements is specified. No general analytical solution is available for this problem, except for the one-dimensional case. Using site-specific thermodynamics, it is shown that the partition function for ligand binding to a two-dimensional lattice can be obtained from those of one-dimensional lattices with known solution. The complexity of the lattice is reduced recursively by application of a contact transformation that involves a relatively small number of steps. The transformation implemented in a computer code solves the partition function of the lattice by operating on the connectivity matrix of the graph associated with it. This provides a powerful new approach to the Ising problem, and enables a systematic analysis of two-dimensional lattices that model many biologically relevant phenomena. Application of this approach to finite two-dimensional lattices with positive cooperativity indicates that the binding capacity per site diverges as Na (N = number of sites in the lattice) and experiences a phase-transition-like discontinuity in the thermodynamic limit N → ∞. The zeroes of the partition function tend to distribute on a slightly distorted unit circle in complex plane and approach the positive real axis already for a 5×5 square lattice. When the lattice has negative cooperativity, its properties mimic those of a system composed of two classes of independent sites with the apparent population of low-affinity binding sites increasing with the size of the lattice, thereby accounting for a phenomenon encountered in many ligand-receptor interactions.

Competition for procurement shares

We propose a new procurement procedure that allocates shares of the total amount to be procured depending on the bids of suppliers. Among the properties of the mechanism are the following: (i) Bidders have an incentive to participate in the procurement procedure, as equilibrium payoffs are strictly positive. (ii) The mechanism allows variations in the extent to which affirmative action objectives, like promoting local industries, are pursued. (iii) Surprisingly, even while accomplishing affirmative action goals, procurement expenditures might be lower than under a standard auction format.

Epistemological Considerations on Systemic Paradigm

This brief study makes some reflections on the systemic paradigm and the claim that Reality is a system advocated by some thinkers. We argue that the General Systems Theory is an abstract theory relating to formal reasons that correspond to real systems scientifically established, and its development can facilitate the task mentioned, which is characteristic of ordinary scientific work.

Some properties of g- and P-spaces

A γ-space with a strictly positive measure is separable. An example of a non-separable γ−space with c.c.c. is given. A P−space with c.c.c. is countable and discrete.

Towards simulation and emulation of large-scale computer networks

Developing analytical models that can accurately describe behaviors of Internet-scale networks is difficult. This is due, in part, to the heterogeneous structure, immense size and rapidly changing properties of today's networks. The lack of analytical models makes large-scale network simulation an indispensable tool for studying immense networks. However, large-scale network simulation has not been commonly used to study networks of Internet-scale. This can be attributed to three factors: 1) current large-scale network simulators are geared towards simulation research and not network research, 2) the memory required to execute an Internet-scale model is exorbitant, and 3) large-scale network models are difficult to validate. This dissertation tackles each of these problems. ^ First, this work presents a method for automatically enabling real-time interaction, monitoring, and control of large-scale network models. Network researchers need tools that allow them to focus on creating realistic models and conducting experiments. However, this should not increase the complexity of developing a large-scale network simulator. This work presents a systematic approach to separating the concerns of running large-scale network models on parallel computers and the user facing concerns of configuring and interacting with large-scale network models. ^ Second, this work deals with reducing memory consumption of network models. As network models become larger, so does the amount of memory needed to simulate them. This work presents a comprehensive approach to exploiting structural duplications in network models to dramatically reduce the memory required to execute large-scale network experiments. ^ Lastly, this work addresses the issue of validating large-scale simulations by integrating real protocols and applications into the simulation. With an emulation extension, a network simulator operating in real-time can run together with real-world distributed applications and services. As such, real-time network simulation not only alleviates the burden of developing separate models for applications in simulation, but as real systems are included in the network model, it also increases the confidence level of network simulation. This work presents a scalable and flexible framework to integrate real-world applications with real-time simulation.^

Foundations of quantitative information flow: Channels, cascades, and the information order

Secrecy is fundamental to computer security, but real systems often cannot avoid leaking some secret information. For this reason, the past decade has seen growing interest in quantitative theories of information flow that allow us to quantify the information being leaked. Within these theories, the system is modeled as an information-theoretic channel that specifies the probability of each output, given each input. Given a prior distribution on those inputs, entropy-like measures quantify the amount of information leakage caused by the channel. ^ This thesis presents new results in the theory of min-entropy leakage. First, we study the perspective of secrecy as a resource that is gradually consumed by a system. We explore this intuition through various models of min-entropy consumption. Next, we consider several composition operators that allow smaller systems to be combined into larger systems, and explore the extent to which the leakage of a combined system is constrained by the leakage of its constituents. Most significantly, we prove upper bounds on the leakage of a cascade of two channels, where the output of the first channel is used as input to the second. In addition, we show how to decompose a channel into a cascade of channels. ^ We also establish fundamental new results about the recently-proposed g-leakage family of measures. These results further highlight the significance of channel cascading. We prove that whenever channel A is composition refined by channel B, that is, whenever A is the cascade of B and R for some channel R, the leakage of A never exceeds that of B, regardless of the prior distribution or leakage measure (Shannon leakage, guessing entropy leakage, min-entropy leakage, or g-leakage). Moreover, we show that composition refinement is a partial order if we quotient away channel structure that is redundant with respect to leakage alone. These results are strengthened by the proof that composition refinement is the only way for one channel to never leak more than another with respect to g-leakage. Therefore, composition refinement robustly answers the question of when a channel is always at least as secure as another from a leakage point of view.^

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.