995 resultados para Frequency Adaptive


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Methods have recently been developed that make use of electromagnetic radiation at terahertz (THz) frequencies, the region of the spectrum between millimetre wavelengths and the infrared, for imaging purposes. Radiation at these wavelengths is non-ionizing and subject to far less Rayleigh scatter than visible or infrared wavelengths, making it suitable for medical applications. This paper introduces THz pulsed imaging and discusses its potential for in vivo medical applications in comparison with existing modalities.

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The speed of convergence while training is an important consideration in the use of neural nets. The authors outline a new training algorithm which reduces both the number of iterations and training time required for convergence of multilayer perceptrons, compared to standard back-propagation and conjugate gradient descent algorithms.

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OBJECTIVE: To determine the effect of altering meal frequency on postprandial lipaemia and associated parameters. DESIGN: A randomized open cross over study to examine the programming effects of altering meal frequency. A standard test meal was given on three occasions following: (i) the normal diet; (ii) a period of two weeks on a nibbling and (iii) a period of two weeks on a gorging diet. SETTING: Free living subjects associated with the University of Surrey. SUBJECTS: Eleven female volunteers (age 22 +/- 0.89 y) were recruited. INTERVENTIONS: The subjects were requested to consume the same foods on either a nibbling diet (12 meals per day) or a gorging diet (three meals per day) for a period of two weeks. The standard test meal containing 80 g fat, 63 g carbohydrate and 20 g protein was administered on the day prior to the dietary intervention and on the day following each period of intervention. MAJOR OUTCOME MEASURES: Fasting and postprandial blood samples were taken for the analysis of plasma triacylglycerol, non-esterified fatty acids, glucose, immunoreactive insulin, glucose-dependent insulinotropic polypeptide levels (GIP) and glucagon-like peptide (GLP-1), fasting total, low density lipoprotein (LDL)- and high density lipoprotein (HDL)-cholesterol concentrations and postheparin lipoprotein lipase (LPL) activity measurements. Plasma paracetamol was measured following administration of a 1.5 g paracetamol load with the meal as an index of gastric emptying. RESULTS: The compliance to the two dietary regimes was high and there were no significant differences between the nutrient intakes on the two intervention diets. There were no significant differences in fasting or postprandial plasma concentrations of triacylglycerol, non-esterified fatty acids, glucose, immunoreactive insulin, GIP and GLP-1 levels, in response to the standard test meal following the nibbling or gorging dietary regimes. There were no significant differences in fasting total or LDL-cholesterol concentrations, or in the 15 min postheparin lipoprotein lipase activity measurements. There was a significant increase in HDL-cholesterol in the subjects following the gorging diet compared to the nibbling diet. DISCUSSION: The results suggest that previous meal frequency for a period of two weeks in young healthy women does not alter the fasting or postprandial lipid or hormonal response to a standard high fat meal. CONCLUSIONS: The findings of this study did not confirm the previous studies which suggested that nibbling is beneficial in reducing the concentrations of lipid and hormones. The rigorous control of diet content and composition in the present study compared with others, suggest reported effects of meal frequency may be due to unintentional alteration in nutrient and energy intake in previous studies.

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In this article, an overview is given of some of the more common approaches taken in applying adaptive control. Gain scheduling, model reference control and self-tuning control are all discussed and in each case suggestions are given for further reading.

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The simulation and development work that has been undertaken to produce a signal equaliser used to improve the data rates from oil well logging instruments is presented. The instruments are lowered into the drill bore hole suspended by a cable which has poor electrical characteristics. The equaliser described in the paper corrects for the distortions that occur from the cable (dispersion and attenuation) with the result that the instrument can send data at 100 K.bits/second down its own suspension cable of 12 Km in length. The use of simulation techniques and tools were invaluable in generating a model for the distortions and proved to be a useful tool when site testing was not available.

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In a decision feedback equalizer (DFE), the structural parameters, including the decision delay, the feedforward filter (FFF), and feedback filter (FBF) lengths, must be carefully chosen, as they greatly influence the performance. Although the FBF length can be set as the channel memory, there is no closed-form expression for the FFF length and decision delay. In this letter, first we analytically show that the two-dimensional search for the optimum FFF length and decision delay can be simplified to a one-dimensional search and then describe a new adaptive DFE where the optimum structural parameters can be self-adapted.

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In an adaptive equaliser, the time lag is an important parameter that significantly influences the performance. Only with the optimum time lag that corresponds to the best minimum-mean-square-error (MMSE) performance, can there be best use of the available resources. Many designs, however, choose the time lag either based on preassumption of the channel or simply based on average experience. The relation between the MMSE performance and the time lag is investigated using a new interpretation of the MMSE equaliser, and then a novel adaptive time lag algorithm is proposed based on gradient search. The proposed algorithm can converge to the optimum time lag in the mean and is verified by the numerical simulations provided.

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The tap-length, or the number of the taps, is an important structural parameter of the linear MMSE adaptive filter. Although the optimum tap-length that balances performance and complexity varies with scenarios, most current adaptive filters fix the tap-length at some compromise value, making them inefficient to implement especially in time-varying scenarios. A novel gradient search based variable tap-length algorithm is proposed, using the concept of the pseudo-fractional tap-length, and it is shown that the new algorithm can converge to the optimum tap-length in the mean. Results of computer simulations are also provided to verify the analysis.

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The Gram-Schmidt (GS) orthogonalisation procedure has been used to improve the convergence speed of least mean square (LMS) adaptive code-division multiple-access (CDMA) detectors. However, this algorithm updates two sets of parameters, namely the GS transform coefficients and the tap weights, simultaneously. Because of the additional adaptation noise introduced by the former, it is impossible to achieve the same performance as the ideal orthogonalised LMS filter, unlike the result implied in an earlier paper. The authors provide a lower bound on the minimum achievable mean squared error (MSE) as a function of the forgetting factor λ used in finding the GS transform coefficients, and propose a variable-λ algorithm to balance the conflicting requirements of good tracking and low misadjustment.

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The blind minimum output energy (MOE) adaptive detector for code division multiple access (CDMA) signals requires exact knowledge of the received spreading code of the desired user. This requirement can be relaxed by constraining the so-called surplus energy of the adaptive tap-weight vector, but the ideal constraint value is not easily obtained in practice. An algorithm is proposed to adaptively track this value and hence to approach the best possible performance for this class of CDMA detector.

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This paper analyzes the convergence behavior of the least mean square (LMS) filter when used in an adaptive code division multiple access (CDMA) detector consisting of a tapped delay line with adjustable tap weights. The sampling rate may be equal to or higher than the chip rate, and these correspond to chip-spaced (CS) and fractionally spaced (FS) detection, respectively. It is shown that CS and FS detectors with the same time-span exhibit identical convergence behavior if the baseband received signal is strictly bandlimited to half the chip rate. Even in the practical case when this condition is not met, deviations from this observation are imperceptible unless the initial tap-weight vector gives an extremely large mean squared error (MSE). This phenomenon is carefully explained with reference to the eigenvalues of the correlation matrix when the input signal is not perfectly bandlimited. The inadequacy of the eigenvalue spread of the tap-input correlation matrix as an indicator of the transient behavior and the influence of the initial tap weight vector on convergence speed are highlighted. Specifically, a initialization within the signal subspace or to the origin leads to very much faster convergence compared with initialization in the a noise subspace.

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The power of an adaptive equalizer is maximized when the structural parameters including the tap-length and decision delay can be optimally chosen. Although the method for adjusting either the tap-length or decision delay has been proposed, adjusting both simultaneously becomes much more involved as they interact with each other. In this paper, this problem is solved by putting a linear prewhitener before the equalizer, with which the equivalent channel becomes maximum-phase. This implies that the optimum decision delay can be simply ¯xed at the tap-length minus one, while the tap-length can then be chosen using a similar approach as that proposed in our previous work.

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This paper discusses the application of model reference adaptive control concepts to the automatic tuning of PID controllers. The effectiveness of the proposed method is shown through simulated applications. The gradient approach and simulated examples are provided.

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This paper describes the application of artificial neural networks for automatic tuning of PID controllers using the Model Reference Adaptive Control approach. The effectiveness of the proposed method is shown through a simulated application.