999 resultados para output convergence


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The multilayer perceptron network has become one of the most used in the solution of a wide variety of problems. The training process is based on the supervised method where the inputs are presented to the neural network and the output is compared with a desired value. However, the algorithm presents convergence problems when the desired output of the network has small slope in the discrete time samples or the output is a quasi-constant value. The proposal of this paper is presenting an alternative approach to solve this convergence problem with a pre-conditioning method of the desired output data set before the training process and a post-conditioning when the generalization results are obtained. Simulations results are presented in order to validate the proposed approach.

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This paper presents an overlapping generations model with physical and human capital and income inequality. It shows that inequality impedes output growth by directly harming capital accumulation and indirectly raising the ratio of physical to human capital. The convergence speed of output growth equals the lower of the convergence speeds of the relative capital ratio and inequality, and varies with initial states. Among economies with the same balanced growth rate but different initial income levels, the ranking of income can switch in favor of those starting from low inequality and a low ratio of physical to human capital, particularly if the growth rate converges slowly. (C) 2004 Elsevier B.V. All rights reserved.

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Background The accurate measurement of Cardiac output (CO) is vital in guiding the treatment of critically ill patients. Invasive or minimally invasive measurement of CO is not without inherent risks to the patient. Skilled Intensive Care Unit (ICU) nursing staff are in an ideal position to assess changes in CO following therapeutic measures. The USCOM (Ultrasonic Cardiac Output Monitor) device is a non-invasive CO monitor whose clinical utility and ease of use requires testing. Objectives To compare cardiac output measurement using a non-invasive ultrasonic device (USCOM) operated by a non-echocardiograhically trained ICU Registered Nurse (RN), with the conventional pulmonary artery catheter (PAC) using both thermodilution and Fick methods. Design Prospective observational study. Setting and participants Between April 2006 and March 2007, we evaluated 30 spontaneously breathing patients requiring PAC for assessment of heart failure and/or pulmonary hypertension at a tertiary level cardiothoracic hospital. Methods SCOM CO was compared with thermodilution measurements via PAC and CO estimated using a modified Fick equation. This catheter was inserted by a medical officer, and all USCOM measurements by a senior ICU nurse. Mean values, bias and precision, and mean percentage difference between measures were determined to compare methods. The Intra-Class Correlation statistic was also used to assess agreement. The USCOM time to measure was recorded to assess the learning curve for USCOM use performed by an ICU RN and a line of best fit demonstrated to describe the operator learning curve. Results In 24 of 30 (80%) patients studied, CO measures were obtained. In 6 of 30 (20%) patients, an adequate USCOM signal was not achieved. The mean difference (±standard deviation) between USCOM and PAC, USCOM and Fick, and Fick and PAC CO were small, −0.34 ± 0.52 L/min, −0.33 ± 0.90 L/min and −0.25 ± 0.63 L/min respectively across a range of outputs from 2.6 L/min to 7.2 L/min. The percent limits of agreement (LOA) for all measures were −34.6% to 17.8% for USCOM and PAC, −49.8% to 34.1% for USCOM and Fick and −36.4% to 23.7% for PAC and Fick. Signal acquisition time reduced on average by 0.6 min per measure to less than 10 min at the end of the study. Conclusions In 80% of our cohort, USCOM, PAC and Fick measures of CO all showed clinically acceptable agreement and the learning curve for operation of the non-invasive USCOM device by an ICU RN was found to be satisfactorily short. Further work is required in patients receiving positive pressure ventilation.

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This paper proposes a novel relative entropy rate (RER) based approach for multiple HMM (MHMM) approximation of a class of discrete-time uncertain processes. Under different uncertainty assumptions, the model design problem is posed either as a min-max optimisation problem or stochastic minimisation problem on the RER between joint laws describing the state and output processes (rather than the more usual RER between output processes). A suitable filter is proposed for which performance results are established which bound conditional mean estimation performance and show that estimation performance improves as the RER is reduced. These filter consistency and convergence bounds are the first results characterising multiple HMM approximation performance and suggest that joint RER concepts provide a useful model selection criteria. The proposed model design process and MHMM filter are demonstrated on an important image processing dim-target detection problem.

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A recent article in the Journal of Science and Medicine in Sport by Chapman et al.1 reported data from an empirical investigation comparing lower extremity joint motions, joint coordination and muscle recruitment in expert and novice cyclists. 3D kinematic and intramuscular electromyographic (EMG) analyses revealed no differences between expert and novice cyclists for normalised joint angles and velocities of the pelvis, hip, knee and ankle. However, significant differences in the strength of sagittal plane kinematics for hip–ankle and knee–ankle joint couplings were reported, with expert cyclists displaying tighter coupling relationships than novice cyclists. Furthermore, significant differences between expert and novice cyclists for all muscle recruitment parameters, except timing of peak EMG amplitude, were also reported.

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This paper presents dynamic hysteresis band height control to reduce the overshoot and undershoot issue on output voltage caused by load change. The converters in this study are Boost and Positive Buck-Boost (PBB) converters. PBB has been controlled to work in a step up conversion and avoid overshoot when load is changed. Simulation and experimental results have been presented to verify the proposed method.

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Efficient and effective urban management systems for Ubiquitous Eco Cities require having intelligent and integrated management mechanisms. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated, transparent and open decision making mechanism and necessary infrastructure and technologies. In Ubiquitous Eco Cities telecommunication technologies play an important role in monitoring and managing activities over wired, wireless or fibre-optic networks. Particularly technology convergence creates new ways in which the information and telecommunication technologies are used and formed the back bone or urban management systems. The 21st Century is an era where information has converged, in which people are able to access a variety of services, including internet and location based services, through multi-functional devices such as mobile phones and provides opportunities in the management of Ubiquitous Eco Cities. This research paper discusses the recent developments in telecommunication networks and trends in convergence technologies and their implications on the management of Ubiquitous Eco Cities and how this technological shift is likely to be beneficial in improving the quality of life and place of residents, workers and visitors. The research paper reports and introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for Ubiquitous Eco Cities.