135 resultados para Constrained Minimization
Resumo:
The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.
Resumo:
The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach.
Resumo:
Regulatory and funding asymmetries in the Spanish motorway network produce huge differences in the structure of gasoline markets by motorway type: free or toll. While competition is encouraged among gas stations on free motorways, the regulations for toll motorways allow private concessionaires to auction all gas stations to the same provider, thereby limiting competition and consolidating market power. This paper reports how this regulatory asymmetry results in higher prices and fewer gas stations. Specifically, we show that competition is constrained on toll motorways by the granting of geographical monopolies, resulting in a small number of rivals operating in close proximity to each other, and allowing gas stations to operate as local monopolies. The lack of competition would seem to account for the price differential between toll and free motorways. According to available evidence, deregulation measures affecting toll motorway concessions could help to mitigate price inefficiencies and increase consumer welfare.
Resumo:
This paper seeks to address the problem of the empirical identification of housing market segmentation,once we assume that submarkets exist. The typical difficulty in identifying housing submarkets when dealing with many locations is the vast number of potential solutions and, in such cases, the use of the Chow test for hedonic functions is not a practical solution. Here, we solve this problem by undertaking an identification process with a heuristic for spatially constrained clustering, the"Housing Submarket Identifier" (HouSI). The solution is applied to the housing market in the city of Barcelona (Spain), where we estimate a hedonic model for fifty thousand dwellings aggregated into ten groups. In order to determine the utility of the procedure we seek to verify whether the final solution provided by the heuristic is comparable with the division of the city into ten administrative districts.
Resumo:
A technique for simultaneous localisation and mapping (SLAM) for large scale scenarios is presented. This solution is based on the use of independent submaps of a limited size to map large areas. In addition, a global stochastic map, containing the links between adjacent submaps, is built. The information in both levels is corrected every time a loop is closed: local maps are updated with the information from overlapping maps, and the global stochastic map is optimised by means of constrained minimisation
Resumo:
An extension of the standard rationing model is introduced. Agents are not only identi fied by their respective claims over some amount of a scarce resource, but also by some payoff thresholds. These thresholds introduce exogenous differences among agents (full or partial priority, past allocations, past debts, ...) that may influence the final distribution. Within this framework we provide generalizations of the constrained equal awards rule and the constrained equal losses rule. We show that these generalized rules are dual from each other. We characterize the generalization of the equal awards rule by using the properties of consistency, path-independence and compensated exemption. Finally, we use the duality between rules to characterize the generalization of the equal losses solution.
Resumo:
Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.
Resumo:
This paper focuses on cooperative games with transferable utility. We propose the computation of two solutions, the Shapley value for n agents and the nucleolus with a maximum of four agents. The current approach is also focused on conflicting claims problems, a particular case of coalitional games. We provide the computation of the most well-known and used claims solutions: the proportional, the constrained equal awards, the constrained equal losses, the Talmud and the random arrival rules. Keywords: Cooperative game, Shapley value, nucleolus, claims problem, claims rule, bankruptcy.
Resumo:
During the first decade of this century, Spain experienced the most important economic and housing boom in its recent history. This situation led the lending industry to dramatically expand through the mortgage market. The high competition among lenders caused a dramatic lowering of credit standards. During this period, lenders operating in the Spanish mortgage market artificially inflated appraised home values in order to draw larger mortgages. By doing this, lenders gave financially constrained households access to mortgage credit. In this paper, we analyze this phenomenon for this first time. To do so, we resort to a unique dataset of matched mortgage-dwelling-borrower characteristics covering the period 2004–2010. Our data allow us to construct an unbiased measure of property’s over-appraisal, since transaction prices in our data also includes any potential side payment in the transactions. Our findings indicate that i) in Spain, appraised home values were inflated on average by around 30% with respect to transaction prices; ii) creditconstrained households were more likely to be involved in mortgages with inflated house values; and iii) a regional indicator of competition in the lending market suggests that inflated appraisal values were also more likely to appear in more competitive regional mortgage markets. Keywords: Housing demand, appraisal values, house prices, housing bubble, credit constraints, mortgage market. JEL Classification: R21, R31
Resumo:
This article is the result of an ongoing research into a variety of features of Spanish local government. It aims, in particular, at providing a profile of the tools implemented by local authorities to improve local democracy in Catalonia. The main hypothesis of the work is that, even though the Spanish local model is constrained by a shared and unique set of legal regulations, local institutions in Catalonia have developed their own model of local participation. And the range of instruments like these is still now increasing. More specifically, the scope of this research is twofold. On the one hand, different types of instruments for public deliberation in the Catalan local administration system are identified and presented, based on the place they take in the policy cycle. On the other hand, we focus on policy domains and the quality of the decision-making processes. Researching the stability of the participation tools or whether local democracy prefers more 'ad hoc' processes allows us to analyze the boundaries/limits of local democracy in Catalonia. The main idea underlying this paper is that, despite the existence of a single legal model regulating municipalities in Catalonia, local authorities tend to use their legally granted selfmanagement capacities to design their own instruments which end up presenting perceivable distinct features, stressing democracy in different policy domains, and in diverse policy cycles. Therefore, this paper is intended to identify such models and to provide factors (variables) so that an explanatory model can be built.
Resumo:
In image processing, segmentation algorithms constitute one of the main focuses of research. In this paper, new image segmentation algorithms based on a hard version of the information bottleneck method are presented. The objective of this method is to extract a compact representation of a variable, considered the input, with minimal loss of mutual information with respect to another variable, considered the output. First, we introduce a split-and-merge algorithm based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output). From this channel, the maximization of the mutual information gain is used to optimize the image partitioning. Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information. From the inversion of the above channel, we also present a new histogram clustering algorithm based on the minimization of the mutual information loss, where now the input variable represents the histogram bins and the output is given by the set of regions obtained from the above split-and-merge algorithm. Finally, we introduce two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned. Different experiments on 2-D and 3-D images show the behavior of the proposed algorithms
Resumo:
Vehicle operations in underwater environments are often compromised by poor visibility conditions. For instance, the perception range of optical devices is heavily constrained in turbid waters, thus complicating navigation and mapping tasks in environments such as harbors, bays, or rivers. A new generation of high-definition forward-looking sonars providing acoustic imagery at high frame rates has recently emerged as a promising alternative for working under these challenging conditions. However, the characteristics of the sonar data introduce difficulties in image registration, a key step in mosaicing and motion estimation applications. In this work, we propose the use of a Fourier-based registration technique capable of handling the low resolution, noise, and artifacts associated with sonar image formation. When compared to a state-of-the art region-based technique, our approach shows superior performance in the alignment of both consecutive and nonconsecutive views as well as higher robustness in featureless environments. The method is used to compute pose constraints between sonar frames that, integrated inside a global alignment framework, enable the rendering of consistent acoustic mosaics with high detail and increased resolution. An extensive experimental section is reported showing results in relevant field applications, such as ship hull inspection and harbor mapping
Resumo:
Feedback-related negativity (FRN) is an ERP component that distinguishes positive from negative feedback. FRN has been hypothesized to be the product of an error signal that may be used to adjust future behavior. In addition, associative learning models assume that the trial-to-trial learning of cueoutcome mappings involves the minimization of an error term. This study evaluated whether FRN is a possible electrophysiological correlate of this error term in a predictive learning task where human subjects were asked to learn different cueoutcome relationships. Specifically, we evaluated the sensitivity of the FRN to the course of learning when different stimuli interact or compete to become a predictor of certain outcomes. Importantly, some of these cues were blocked by more informative or predictive cues (i.e., the blocking effect). Interestingly, the present results show that both learning and blocking affect the amplitude of the FRN component. Furthermore, independent analyses of positive and negative feedback event-related signals showed that the learning effect was restricted to the ERP component elicited by positive feedback. The blocking test showed differences in the FRN magnitude between a predictive and a blocked cue. Overall, the present results show that ERPs that are related to feedback processing correspond to the main predictions of associative learning models. ■
Resumo:
An important issue in language learning is how new words are integrated in the brain representations that sustain language processing. To identify the brain regions involved in meaning acquisition and word learning, we conducted a functional magnetic resonance imaging study. Young participants were required to deduce the meaning of a novel word presented within increasingly constrained sentence contexts that were read silently during the scanning session. Inconsistent contexts were also presented in which no meaning could be assigned to the novel word. Participants showed meaning acquisition in the consistent but not in the inconsistent condition. A distributed brain network was identified comprising the left anterior inferior frontal gyrus (BA 45), the middle temporal gyrus (BA 21), the parahippocampal gyrus, and several subcortical structures (the thalamus and the striatum). Drawing on previous neuroimaging evidence, we tentatively identify the roles of these brain areas in the retrieval, selection, and encoding of the meaning.
Resumo:
En aquests últims anys, són moltes les empreses que han optat per la utilització de sistemes de gestió normalitzats, per a garantir la rendibilitat i fiabilitat dels resultats de la implantació del sistema de gestió en qüestió. A la dècada dels 90 va ser quan la implantació de sistemes de gestió va començar a ser important en la majoria de sectors econòmics. L’evolució en els sistemes de gestió a trets generals va iniciar-se primerament en l’àmbit de la qualitat, seguidament en la gestió ambiental i en última instància en la prevenció de riscos laborals. Aquests tres tipus de sistemes de gestió, en els últims anys s’han anat integrant, de manera que s’han reduït els recursos i els esforços emprats en la gestió, millorant significativament l’eficàcia i l’eficiència d’aquests sistemes. L’objectiu principal que persegueix aquest projecte, és definir un sistema de gestió que permeti a l’empresa conduir les seves activitats de forma simplificada i ordenada, i que alhora faciliti la informació necessària per a corregir i millorar les activitats. Un altre objectiu que pretén aconseguir aquest projecte, és el de dissenyar un SGI que aprofiti les sinèrgies generades en els diferents àmbits de la pròpia empresa i fomenti les interaccions entre els diferents nivells de l’organització. En conseqüència, millorarà de forma important els fluxos d’informació dins de l’empresa minimitzant els esforços i la pèrdua d’informació. El mètode escollit per a la implantació del SGI, ha estat la Gestió per Processos, la qual es basa en la definició i seguiment dels processos de l’empresa, partint de les necessitats del client i acabant quan aquestes estan satisfetes. En conclusió, a la finalització del present projecte s’obtindrà un SGI, amb tots els processos de l’empresa definits i implantats, que doni compliment a les normes UNEEN-ISO 9001:00, UNE-EN-ISO 14001:04 i OHSAS 18001:07. Aquest SGI, que s’ha realitzat des d’un punt de vista documental i teòric, suposarà una millora de l’eficàcia operativa dels processos i una important millora competitiva de l’empresa.