22 resultados para feed restriction

em Aston University Research Archive


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The performance of feed-forward neural networks in real applications can be often be improved significantly if use is made of a-priori information. For interpolation problems this prior knowledge frequently includes smoothness requirements on the network mapping, and can be imposed by the addition to the error function of suitable regularization terms. The new error function, however, now depends on the derivatives of the network mapping, and so the standard back-propagation algorithm cannot be applied. In this paper, we derive a computationally efficient learning algorithm, for a feed-forward network of arbitrary topology, which can be used to minimize the new error function. Networks having a single hidden layer, for which the learning algorithm simplifies, are treated as a special case.

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In this paper we consider four alternative approaches to complexity control in feed-forward networks based respectively on architecture selection, regularization, early stopping, and training with noise. We show that there are close similarities between these approaches and we argue that, for most practical applications, the technique of regularization should be the method of choice.

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This thesis is a study of the generation of topographic mappings - dimension reducing transformations of data that preserve some element of geometric structure - with feed-forward neural networks. As an alternative to established methods, a transformational variant of Sammon's method is proposed, where the projection is effected by a radial basis function neural network. This approach is related to the statistical field of multidimensional scaling, and from that the concept of a 'subjective metric' is defined, which permits the exploitation of additional prior knowledge concerning the data in the mapping process. This then enables the generation of more appropriate feature spaces for the purposes of enhanced visualisation or subsequent classification. A comparison with established methods for feature extraction is given for data taken from the 1992 Research Assessment Exercise for higher educational institutions in the United Kingdom. This is a difficult high-dimensional dataset, and illustrates well the benefit of the new topographic technique. A generalisation of the proposed model is considered for implementation of the classical multidimensional scaling (¸mds}) routine. This is related to Oja's principal subspace neural network, whose learning rule is shown to descend the error surface of the proposed ¸mds model. Some of the technical issues concerning the design and training of topographic neural networks are investigated. It is shown that neural network models can be less sensitive to entrapment in the sub-optimal global minima that badly affect the standard Sammon algorithm, and tend to exhibit good generalisation as a result of implicit weight decay in the training process. It is further argued that for ideal structure retention, the network transformation should be perfectly smooth for all inter-data directions in input space. Finally, there is a critique of optimisation techniques for topographic mappings, and a new training algorithm is proposed. A convergence proof is given, and the method is shown to produce lower-error mappings more rapidly than previous algorithms.

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The effects of haem limitation and iron restriction on cells of non typable Haemophilus influenzae were investigated. Haem limitation was achieved by adding concentrations of haem to growth media which resulted in substantial decreases in final cell yields. Iron restriction was achieved by substituting protoporphyrin IX (PPIX) for haem in the growth medium and adding an iron chelator to the system. The effect of these nutrient limitations on a) outer membrane composition, and b) respiratory systems of non typable H.influenzae was investigated. Several of the strains examined produced new PPIX-specific outer membrane proteins when cultured utilising PPIX as a porphyrin source. The immune response of patients with bronchiectasis to outer membrane antigens of H.influenzae cultured under iron-restricted conditions was analysed by ELISA and immunoblotting techniques. ELISA analysis revealed that individuals with severe bronchiectasis had high titres of antibodies directed against H.influenzae OMs in both serum and sputum. Immunoblotting with homologous serum showed that where PPIX-specific OMPs were produced they were antigenic and were recognised by patients' serum. This suggested that these H.influenzae OMPs may be expressed in vivo. Additionally, the development of the immune responses to non typable H.influenzae outer membrane antigens was investigated using a rat lung model. Bacteria encased in agar beads were inoculated intratracheally into rat lungs, infection was established, and the immune response monitored for 6 weeks. The animals developed antibodies to PPIX-specific OMPs during the course of infection, providing further evidence that H.influenzae express these novel OMP antigens when growing in vivo. Studies in vitro on respiratory systems of phenotypically altered H.influenzae showed that bacteria grown utilising PPIX as a porphyrin source, or under conditions of iron-restriction produced ten fold fewer cytochromes than cells grown in nutrient excess, while haem limited H.influenzae produced no detectable cytochromes. Respiration of various substrates was depressed in haem limited and in PPIX-grown cultures as compared with cells grown in nutrient excess.

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We report a novel real-time homodyne coherent receiver based on a DPSK optical-electrical-optical (OEO) regenerator used to extract a carrier from carrier-less phase modulated signals based on feed-forward based modulation stripping. The performance of this non-DSP based coherent receiver was evaluated for 10.66Gbit/s BPSK signals. Self-homodyne coherent detection and homodyne detection with an injection-locked local oscillator laser was demonstrated. The performance was evaluated by measuring the electrical signal-to-noise (SNR) and recording the eye diagrams. Using injection-locking for the LO improves the performance and enables homodyne detection with optical injection-locking to operate with carrier-less BPSK signals without the need for polarization multiplexed pilot-tones.

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We experimentally demonstrate a novel synchronous 10.66Gbit/s DPSK OEO regenerator which uses a feed-forward carrier extraction scheme with an injection-locked laser to synchronize the regenerated signal wavelength to the incoming signal wavelength. After injection-locking, a low-cost DFB laser used at the regenerator exhibited the same linewidth characteristics as the narrow line-width transmitter laser. The phase regeneration properties of the regenerator were evaluated by emulating random Gaussian phase noise applied to the DPSK signal before the regenerator using a phase modulator driven by an arbitrary waveform generator. The overall performance was evaluated in terms of electrical eye-diagrams, BER measurements, and constellation diagrams.

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We numerically investigate the combination of full-field detection and feed-forward equalizer (FFE) for adaptive chromatic dispersion compensation up to 2160 km in a 10 Gbit/s on-off keyed optical transmission system. The technique, with respect to earlier reports, incorporates several important implementation modules, including the algorithm for adaptive equalization of the gain imbalance between the two receiver chains, compensation of phase misalignment of the asymmetric Mach-Zehnder interferometer, and simplified implementation of field calculation. We also show that in addition to enabling fast adaptation and simplification of field calculation, full-field FFE exhibits enhanced tolerance to the sampling phase misalignment and reduced sampling rate when compared to the full-field implementation using a dispersive transmission line.

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In their policy proposals on how best to stimulate economic growth, economists have been increasingly emphasizing free markets. It is, however, possible that free-market-led economic growth can lead to increased income inequity which can further increase poverty. One of the more interesting but thus far insufficiently explored mechanisms for the latter is food–feed competition. Using Peruvian Living Standard Survey (PLSS) data for 1985–86 and 1990, the paper examines the demand patterns of households and concludes that the empirical evidence is in agreement with the hypotheses underlying the theory of food–feed competition.

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Direct-drive linear reciprocating compressors offer numerous advantages over conventional counterparts which are usually driven by a rotary induction motor via a crank shaft. However, to ensure efficient and reliable operation under all conditions, it is essential that motor current of a linear compressor follows a sinusoidal current command with a frequency which matches the system resonant frequency. The design of a high-performance current controller for linear compressor drive presents a challenge since the system is highly nonlinear, and an effective solution must be low cost. In this paper, a learning feed-forward current controller for the linear compressors is proposed. It comprises a conventional feedback proportional-integral controller and a feed-forward B-spline neural network (BSNN). The feed-forward BSNN is trained online and in real time in order to minimize the current tracking error. Extensive simulation and experiment results with a prototype linear compressor show that the proposed current controller exhibits high steady state and transient performance. © 2009 IEEE.

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A recent novel approach to the visualisation and analysis of datasets, and one which is particularly applicable to those of a high dimension, is discussed in the context of real applications. A feed-forward neural network is utilised to effect a topographic, structure-preserving, dimension-reducing transformation of the data, with an additional facility to incorporate different degrees of associated subjective information. The properties of this transformation are illustrated on synthetic and real datasets, including the 1992 UK Research Assessment Exercise for funding in higher education. The method is compared and contrasted to established techniques for feature extraction, and related to topographic mappings, the Sammon projection and the statistical field of multidimensional scaling.

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Purpose: Prenatal undernutrition followed by postweaning feeding of a high-fat diet results in obesity in the adult offspring. In this study, we investigated whether diet-induced thermogenesis is altered as a result of such nutritional mismatch. Methods: Female MF-1 mice were fed a normal protein (NP, 18 % casein) or a protein-restricted (PR, 9 % casein) diet throughout pregnancy and lactation. After weaning, male offspring of both groups were fed either a high-fat diet (HF; 45 % kcal fat) or standard chow (C, 7 % kcal fat) to generate the NP/C, NP/HF, PR/C and PR/HF adult offspring groups (n = 7-11 per group). Results: PR/C and NP/C offspring have similar body weights at 30 weeks of age. Postweaning HF feeding resulted in significantly heavier NP/HF offspring (P <0.01), but not in PR/HF offspring, compared with their chow-fed counterparts. However, the PR/HF offspring exhibited greater adiposity (P <0.01) v the NP/HF group. The NP/HF offspring had increased energy expenditure and increased mRNA expression of uncoupling protein-1 and β-3 adrenergic receptor in the interscapular brown adipose tissue (iBAT) compared with the NP/C mice (both at P <0.01). No such differences in energy expenditure and iBAT gene expression were observed between the PR/HF and PR/C offspring. Conclusions: These data suggest that a mismatch between maternal diet during pregnancy and lactation, and the postweaning diet of the offspring, can attenuate diet-induced thermogenesis in the iBAT, resulting in the development of obesity in adulthood. © 2014 Springer-Verlag Berlin Heidelberg.