934 resultados para Minimum Entropy Deconvolution
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In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the cross-entropy method in the context of continuous optimization. We demonstrate the effectiveness of the cross-entropy method for solving difficult continuous multi-extremal optimization problems, including those with non-linear constraints.
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We present theoretical predictions for the equation of state of a harmonically trapped Fermi gas in the unitary limit. Our calculations compare Monte Carlo results with the equation of state of a uniform gas using three distinct perturbation schemes. We show that in experiments the temperature can be usefully calibrated by making use of the entropy, which is invariant during an adiabatic conversion into the weakly interacting limit of molecular BEC. We predict the entropy dependence of the equation of state.
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This work presents closed form solutions for fully developed temperature distribution and entropy generation due to forced convection in microelectromechanical systems (MEMS) in the Slip-flow regime, for which the Knudsen number lies within the range 0.001
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Relationships between clustering, description length, and regularisation are pointed out, motivating the introduction of a cost function with a description length interpretation and the unusual and useful property of having its minimum approximated by the densest mode of a distribution. A simple inverse kinematics example is used to demonstrate that this property can be used to select and learn one branch of a multi-valued mapping. This property is also used to develop a method for setting regularisation parameters according to the scale on which structure is exhibited in the training data. The regularisation technique is demonstrated on two real data sets, a classification problem and a regression problem.
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Using techniques from Statistical Physics, the annealed VC entropy for hyperplanes in high dimensional spaces is calculated as a function of the margin for a spherical Gaussian distribution of inputs.
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The concept of entropy rate is well defined in dynamical systems theory but is impossible to apply it directly to finite real world data sets. With this in mind, Pincus developed Approximate Entropy (ApEn), which uses ideas from Eckmann and Ruelle to create a regularity measure based on entropy rate that can be used to determine the influence of chaotic behaviour in a real world signal. However, this measure was found not to be robust and so an improved formulation known as the Sample Entropy (SampEn) was created by Richman and Moorman to address these issues. We have developed a new, related, regularity measure which is not based on the theory provided by Eckmann and Ruelle and proves a more well-behaved measure of complexity than the previous measures whilst still retaining a low computational cost.
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Conventional feed forward Neural Networks have used the sum-of-squares cost function for training. A new cost function is presented here with a description length interpretation based on Rissanen's Minimum Description Length principle. It is a heuristic that has a rough interpretation as the number of data points fit by the model. Not concerned with finding optimal descriptions, the cost function prefers to form minimum descriptions in a naive way for computational convenience. The cost function is called the Naive Description Length cost function. Finding minimum description models will be shown to be closely related to the identification of clusters in the data. As a consequence the minimum of this cost function approximates the most probable mode of the data rather than the sum-of-squares cost function that approximates the mean. The new cost function is shown to provide information about the structure of the data. This is done by inspecting the dependence of the error to the amount of regularisation. This structure provides a method of selecting regularisation parameters as an alternative or supplement to Bayesian methods. The new cost function is tested on a number of multi-valued problems such as a simple inverse kinematics problem. It is also tested on a number of classification and regression problems. The mode-seeking property of this cost function is shown to improve prediction in time series problems. Description length principles are used in a similar fashion to derive a regulariser to control network complexity.
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There has been much recent research into extracting useful diagnostic features from the electrocardiogram with numerous studies claiming impressive results. However, the robustness and consistency of the methods employed in these studies is rarely, if ever, mentioned. Hence, we propose two new methods; a biologically motivated time series derived from consecutive P-wave durations, and a mathematically motivated regularity measure. We investigate the robustness of these two methods when compared with current corresponding methods. We find that the new time series performs admirably as a compliment to the current method and the new regularity measure consistently outperforms the current measure in numerous tests on real and synthetic data.
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The sectoral and occupational structure of Britain and West Germany has increasingly changed over the last fifty years from a manual manufacturing based to a non-manual service sector based one. There has been a trend towards more managerial and less menial type occupations. Britain employs a higher proportion of its population in the service sector than in manufacturing compared to West Germany, except in retailing, where West Germany employs twice as many people as Britain. This is a stable sector of the economy in terms of employment, but the requirements of the workforce have changed in line with changes in the industry in both countries. School leavers in the two countries, faced with the same options (FE, training schemes or employment) have opted for the various options in different proportions: young Germans are staying longer in education before embarking on training and young Britons are now less likely to go straight into employment than ten years ago. Training is becoming more accepted as the normal route into employment with government policy leading the way, but public opinion still slow to respond. This study investigates how vocational training has adapted to the changing requirements of industry, often determined by technological advancements. In some areas e.g. manufacturing industry the changes have been radical, in others such as retailing they have not, but skill requirements, not necessarily influenced by technology have changed. Social-communicative skills, frequently not even considered skills and therefore not included in training are coming to the forefront. Vocational training has adapted differently in the two countries: in West Germany on the basis of an established over-defined system and in Britain on the basis of an out-dated ill-defined and almost non-existent system. In retailing German school leavers opt for two or three year apprenticeships whereas British school leavers are offered employment with or without formalised training. The publicly held view of the occupation of sales assistant is one of low-level skill, low intellectual demands and a job anyone can do. The traditional skills - product knowledge, selling and social-communicative skills have steadily been eroded. In the last five years retailers have recognised that a return to customer service, utilising the traditional skills was going to be needed of their staff to remain competitive. This requires training. The German retail training system responded by adapting its training regulations in a long consultative process, whereas the British experimented with YTS, a formalised training scheme nationwide being a new departure. The thesis evaluates the changes in these regulations. The case studies in four retail outlets demonstrate that it is indeed product knowledge and selling and social-communicative skills which are fundamental to being a successful and content sales assistant in either country. When the skills are recognised and taught well and systematically the foundations for career development in retailing are laid in a labour market which is continually looking for better qualified workers. Training, when planned and conducted professionally is appreciated by staff and customers and of benefit to the company. In retailing not enough systematic training, to recognisable standards is carried out in Britain, whereas in West Germany the training system is nevertheless better prepared to show innovative potential as a structure and is in place on which to build. In Britain the reputation of the individual company has a greater role to play, not ensuring a national provision of good training in retailing.
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In this study, a new entropy measure known as kernel entropy (KerEnt), which quantifies the irregularity in a series, was applied to nocturnal oxygen saturation (SaO 2) recordings. A total of 96 subjects suspected of suffering from sleep apnea-hypopnea syndrome (SAHS) took part in the study: 32 SAHS-negative and 64 SAHS-positive subjects. Their SaO 2 signals were separately processed by means of KerEnt. Our results show that a higher degree of irregularity is associated to SAHS-positive subjects. Statistical analysis revealed significant differences between the KerEnt values of SAHS-negative and SAHS-positive groups. The diagnostic utility of this parameter was studied by means of receiver operating characteristic (ROC) analysis. A classification accuracy of 81.25% (81.25% sensitivity and 81.25% specificity) was achieved. Repeated apneas during sleep increase irregularity in SaO 2 data. This effect can be measured by KerEnt in order to detect SAHS. This non-linear measure can provide useful information for the development of alternative diagnostic techniques in order to reduce the demand for conventional polysomnography (PSG). © 2011 IEEE.
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Using a well-established analytic nonlinear signal-to-noise ratio noise model we show that there are very simple, fibre independent, amplifier gains which minimize the total energy requirement for amplified systems. Power savings of over 50% are shown to be possible by choosing appropriate amplifier gain and output power.