94 resultados para Neural Networks, Hardware, In-The-Loop Training


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A new PID tuning and controller approach is introduced for Hammerstein systems based on input/output data. A B-spline neural network is used to model the nonlinear static function in the Hammerstein system. The control signal is composed of a PID controller together with a correction term. In order to update the control signal, the multistep ahead predictions of the Hammerstein system based on the B-spline neural networks and the associated Jacobians matrix are calculated using the De Boor algorithms including both the functional and derivative recursions. A numerical example is utilized to demonstrate the efficacy of the proposed approaches.

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Simulating spiking neural networks is of great interest to scientists wanting to model the functioning of the brain. However, large-scale models are expensive to simulate due to the number and interconnectedness of neurons in the brain. Furthermore, where such simulations are used in an embodied setting, the simulation must be real-time in order to be useful. In this paper we present NeMo, a platform for such simulations which achieves high performance through the use of highly parallel commodity hardware in the form of graphics processing units (GPUs). NeMo makes use of the Izhikevich neuron model which provides a range of realistic spiking dynamics while being computationally efficient. Our GPU kernel can deliver up to 400 million spikes per second. This corresponds to a real-time simulation of around 40 000 neurons under biologically plausible conditions with 1000 synapses per neuron and a mean firing rate of 10 Hz.

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This paper compares the performance of artificial neural networks (ANNs) with that of the modified Black model in both pricing and hedging Short Sterling options. Using high frequency data, standard and hybrid ANNs are trained to generate option prices. The hybrid ANN is significantly superior to both the modified Black model and the standard ANN in pricing call and put options. Hedge ratios for hedging Short Sterling options positions using Short Sterling futures are produced using the standard and hybrid ANN pricing models, the modified Black model, and also standard and hybrid ANNs trained directly on the hedge ratios. The performance of hedge ratios from ANNs directly trained on actual hedge ratios is significantly superior to those based on a pricing model, and to the modified Black model.

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An important constraint on how hemodynamic neuroimaging signals such as fMRI can be interpreted in terms of the underlying evoked activity is an understanding of neurovascular coupling mechanisms that actually generate hemodynamic responses. The predominant view at present is that the hemodynamic response is most correlated with synaptic input and subsequent neural processing rather than spiking output. It is still not clear whether input or processing is more important in the generation of hemodynamics responses. In order to investigate this we measured the hemodynamic and neural responses to electrical whisker pad stimuli in rat whisker barrel somatosensory cortex both before and after the local cortical injections of the GABAA agonist muscimol. Muscimol would not be expected to affect the thalamocortical input into the cortex but would inhibit subsequent intra-cortical processing. Pre-muscimol infusion whisker stimuli elicited the expected neural and accompanying hemodynamic responses to that reported previously. Following infusion of muscimol, although the temporal profile of neural responses to each pulse of the stimulus train was similar, the average response was reduced in magnitude by ∼79% compared to that elicited pre-infusion. The whisker-evoked hemodynamic responses were reduced by a commensurate magnitude suggesting that, although the neurovascular coupling relationships were similar for synaptic input as well as for cortical processing, the magnitude of the overall response is dominated by processing rather than from that produced from the thalamocortical input alone.

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Although promise exists for patterns of resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) brain connectivity to be used as biomarkers of early brain pathology, a full understanding of the nature of the relationship between neural activity and spontaneous fMRI BOLD fluctuations is required before such data can be correctly interpreted. To investigate this issue, we combined electrophysiological recordings of rapid changes in multi-laminar local field potentials from the somatosensory cortex of anaesthetized rats with concurrent two-dimensional optical imaging spectroscopy measurements of resting-state haemodynamics that underlie fluctuations in the BOLD fMRI signal. After neural ‘events’ were identified, their time points served to indicate the start of an epoch in the accompanying haemodynamic fluctuations. Multiple epochs for both neural ‘events’ and the accompanying haemodynamic fluctuations were averaged. We found that the averaged epochs of resting-state haemodynamic fluctuations taken after neural ‘events’ closely resembled the temporal profile of stimulus-evoked cortical haemodynamics. Furthermore, we were able to demonstrate that averaged epochs of resting-state haemodynamic fluctuations resembling the temporal profile of stimulus-evoked haemodynamics could also be found after peaks in neural activity filtered into specific electroencephalographic frequency bands (theta, alpha, beta, and gamma). This technique allows investigation of resting-state neurovascular coupling using methodologies that are directly comparable to that developed for investigating stimulus-evoked neurovascular responses.

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Many in vitro systems used to examine multipotential neural progenitor cells (NPCs) rely on mitogens including fibroblast growth factor 2 (FGF2) for their continued expansion. However, FGF2 has also been shown to alter the expression of transcription factors (TFs) that determine cell fate. Here, we report that NPCs from the embryonic telencephalon grown without FGF2 retain many of their in vivo characteristics, making them a good model for investigating molecular mechanisms involved in cell fate specification and differentiation. However, exposure of cortical NPCs to FGF2 results in a profound change in the types of neurons generated, switching them from a glutamatergic to a GABAergic phenotype. This change closely correlates with the dramatic upregulation of TFs more characteristic of ventral telencephalic NPCs. In addition, exposure of cortical NPCs to FGF2 maintains their neurogenic potential in vitro, and NPCs spontaneously undergo differentiation following FGF2 withdrawal. These results highlight the importance of TFs in determining the types of neurons generated by NPCs in vitro. In addition, they show that FGF2, as well as acting as a mitogen, changes the developmental capabilities of NPCs. These findings have implications for the cell fate specification of in vitro-expanded NPCs and their ability to generate specific cell types for therapeutic applications. Disclosure of potential conflicts of interest is found at the end of this article.

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This paper reports part of a qualitative study into evolving practice in the implementation of the Dispute Adjudication Board (DAB) construction dispute resolution technique, a variant of the Dispute Review Board (DRB) concept used in the US and Canada. Data was collected through a focus group interview of 20 highly experienced dispute resolution practitioners from engineering and the law. The group was assembled from members of FIDIC-NET with direct experience of project DABs. The part reported here concerns practice and procedure for establishing DABs. The main findings are that: constitution of the DABs is often delayed because of either project owners' ignorance of the DAB process or deterrence by the cost of the DABs; such owners also tend to insist on appointing DAB members from local engineers and lawyers without sufficient understanding of the DAB process; rates of remuneration of DAB members vary widely; the training provision for DAB membership and advocacy skills is inadequate; the process of selecting candidates for DAB membership and negotiating the tripartite agreement between each member and the contractual parties needs to be navigated with great care to avoid raising ethical problems. The research contribution is threefold. First, it highlights the importance of realistic fees for DAB members within a standard framework in achieving timely establishment of a board that works well as a team. Second, it illustrates the use of qualitative focus group interview to study the impact of new contract terms from multiple stakeholder perspectives. Finally, it identifies areas where further research is needed.

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Infant faces elicit early, specific activity in the orbitofrontal cortex (OFC), a key cortical region for reward and affective processing. A test of the causal relationship between infant facial configuration and OFC activity is provided by naturally occurring disruptions to the face structure. One such disruption is cleft lip, a small change to one facial feature, shown to disrupt parenting. Using magnetoencephalography, we investigated neural responses to infant faces with cleft lip compared with typical infant and adult faces. We found activity in the right OFC at 140 ms in response to typical infant faces but diminished activity to infant faces with cleft lip or adult faces. Activity in the right fusiform face area was of similar magnitude for typical adult and infant faces but was significantly lower for infant faces with cleft lip. This is the first evidence that a minor change to the infant face can disrupt neural activity potentially implicated in caregiving.

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The Plaut, McClelland, Seidenberg and Patterson (1996) connectionist model of reading was evaluated at two points early in its training against reading data collected from British children on two occasions during their first year of literacy instruction. First, the network’s non-word reading was poor relative to word reading when compared with the children. Second, the network made more non-lexical than lexical errors, the opposite pattern to the children. Three adaptations were made to the training of the network to bring it closer to the learning environment of a child: an incremental training regime was adopted; the network was trained on grapheme– phoneme correspondences; and a training corpus based on words found in children’s early reading materials was used. The modifications caused a sharp improvement in non-word reading, relative to word reading, resulting in a near perfect match to the children’s data on this measure. The modified network, however, continued to make predominantly non-lexical errors, although evidence from a small-scale implementation of the full triangle framework suggests that this limitation stems from the lack of a semantic pathway. Taken together, these results suggest that, when properly trained, connectionist models of word reading can offer insights into key aspects of reading development in children.

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Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

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Functional brain imaging studies have shown abnormal neural activity in individuals recovered from anorexia nervosa (AN) during both cognitive and emotional task paradigms. It has been suggested that this abnormal activity which persists into recovery might underpin the neurobiology of the disorder and constitute a neural biomarker for AN. However, no study to date has assessed functional changes in neural networks in the absence of task-induced activity in those recovered from AN. Therefore, the aim of this study was to investigate whole brain resting state functional connectivity in nonmedicated women recovered from anorexia nervosa. Functional magnetic resonance imaging scans were obtained from 16 nonmedicated participants recovered from anorexia nervosa and 15 healthy control participants. Independent component analysis revealed functionally relevant resting state networks. Dual regression analysis revealed increased temporal correlation (coherence) in the default mode network (DMN) which is thought to be involved in self-referential processing. Specifically, compared to healthy control participants the recovered anorexia nervosa participants showed increased temporal coherence between the DMN and the precuneus and the dorsolateral prefrontal cortex/inferior frontal gyrus. The findings support the view that dysfunction in resting state functional connectivity in regions involved in self-referential processing and cognitive control might be a vulnerability marker for the development of anorexia nervosa.

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The current work discusses the compositional analysis of spectra that may be related to amorphous materials that lack discernible Lorentzian, Debye or Drude responses. We propose to model such response using a 3-dimensional random RLC network using a descriptor formulation which is converted into an input-output transfer function representation. A wavelet identification study of these networks is performed to infer the composition of the networks. It was concluded that wavelet filter banks enable a parsimonious representation of the dynamics in excited randomly connected RLC networks. Furthermore, chemometric classification using the proposed technique enables the discrimination of dielectric samples with different composition. The methodology is promising for the classification of amorphous dielectrics.

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The current study discusses new opportunities for secure ground to satellite communications using shaped femtosecond pulses that induce spatial hole burning in the atmosphere for efficient communications with data encoded within super-continua generated by femtosecond pulses. Refractive index variation across the different layers in the atmosphere may be modelled using assumptions that the upper strata of the atmosphere and troposphere behaving as layered composite amorphous dielectric networks composed of resistors and capacitors with different time constants across each layer. Input-output expressions of the dynamics of the networks in the frequency domain provide the transmission characteristics of the propagation medium. Femtosecond pulse shaping may be used to optimize the pulse phase-front and spectral composition across the different layers in the atmosphere. A generic procedure based on evolutionary algorithms to perform the pulse shaping is proposed. In contrast to alternative procedures that would require ab initio modelling and calculations of the propagation constant for the pulse through the atmosphere, the proposed approach is adaptive, compensating for refractive index variations along the column of air between the transmitter and receiver.

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This article examines the network relationships of a set of large retail multinational enterprises (MNEs). We analyze under what conditions a flagship-network strategy (characterized by a network of five partners – the MNE, key suppliers, key partners, selected competitors and key organisations in the non-business infrastructure) explains the internationalisation of three retailers whose geographic scope, sectoral conditions and competitive strategies differ substantially. We explore why and when retailers will adopt a flagship strategy. The three firms are two U.K.-based multinational retailers (Tesco and The Body Shop) and a French-based global retailer (Moët Hennessy Louis Vuitton). We find evidence of strong network relationships for all three retailers, although each embraces network strategies for different reasons. Their flagship relationships depend on each retailer's strategic use of firm-specific-advantages (FSAs) and country-specific advantages (CSAs). We find that a flagship strategy can succeed in overcoming internal and/or environmental constraints to cross-border resource transfers, which are barriers to foreign direct investment (FDI). We provide recommendations on why and when to use a flagship-based strategy and which type of network partners to prioritize in order to succeed internationally.

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Neural stem cells are precursors of neurons and glial cells. During brain development, these cells proliferate, migrate and differentiate into specific lineages. Recently neural stem cells within the adult central nervous system were identified. Informations are now emerging about regulation of stem cell proliferation, migration and differentiation by numerous soluble factors such as chemokines and cytokines. However, the signal transduction mechanisms downstream of these factors are less clear. Here, we review potential evidences for a novel central role of the transcription factor nuclear factor kappa B (NF-kappaB) in these crucial signal transduction processes. NF-kappaB is an inducible transcription factor detected in neurons, glia and neural stem cells. NF-kappaB was discovered by David Baltimore's laboratory as a transcription factor in lymphocytes. NF-kappaB is involved in many biological processes such as inflammation and innate immunity, development, apoptosis and anti-apoptosis. It has been recently shown that members of the NF-kappaB family are widely expressed by neurons, glia and neural stem cells. In the nervous system, NF-kappaB plays a crucial role in neuronal plasticity, learning, memory consolidation, neuroprotection and neurodegeneration. Recent data suggest an important role of NF-kappaB on proliferation, migration and differentiation of neural stem cells. NF-kappaB is composed of three subunits: two DNA-binding and one inhibitory subunit. Activation of NF-kappaB takes place in the cytoplasm and results in degradation of the inhibitory subunit, thus enabling the nuclear import of the DNA-binding subunits. Within the nucleus, several target genes could be activated. In this review, we suggest a model explaining the multiple action of NF-kappaB on neural stem cells. Furthermore, we discuss the potential role of NF-kappaB within the so-called brain cancer stem cells.