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Stochastic Digital Backpropagation with Residual Memory Compensation
, 2016
"... AbstractStochastic digital backpropagation (SDBP) is an extension of digital backpropagation (DBP) and is based on the maximum a posteriori principle. SDBP takes into account noise from the optical amplifiers in addition to handling deterministic linear and nonlinear impairments. The decisions in ..."
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in SDBP are taken on a symbolbysymbol (SBS) basis, ignoring any residual memory, which may be present due to nonoptimal processing in SDBP. In this paper, we extend SDBP to account for memory between symbols. In particular, two different methods are proposed: a Viterbi algorithm (VA) and a decision
Residual Algorithms: Reinforcement Learning with Function Approximation
 In Proceedings of the Twelfth International Conference on Machine Learning
, 1995
"... A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that these algorithms can easily become unstable when implemented directly with a general functionapproximation system, such ..."
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Cited by 307 (6 self)
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, such as a sigmoidal multilayer perceptron, a radialbasisfunction system, a memorybased learning system, or even a linear functionapproximation system. A new class of algorithms, residual gradient algorithms, is proposed, which perform gradient descent on the mean squared Bellman residual, guaranteeing
Memory for goals: an activationbased model
, 2002
"... Goaldirected cognition is often discussed in terms of specialized memory structures like the "goal stack." The goalactivation model presented here analyzes goaldirected cognition in terms of the general memory constructs of activation and associative priming. The model embodies three pr ..."
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Cited by 188 (37 self)
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predictive constraints: (1) the interference level, which arises from residual memory for old goals; (1) the strengthening constraint, which makes predictions about time to encode a new goal; and (3) the priming constraint, which makes predictions about the role of cues in retrieving pending goals
Mephedrone in Adolescent Rats: Residual Memory Impairment and Acute but Not Lasting 5HT Depletion
"... Mephedrone (4methylmethcathinone, MMC) is a popular recreational drug, yet its potential harms are yet to be fully established. The current study examined the impact of single or repeated MMC exposure on various neurochemical and behavioral measures in rats. In Experiment 1 male adolescent Wistar r ..."
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. Autoradiographic analysis showed no signs of neuroinflammation ([125I]CLINDE ligand used as a marker for translocator protein (TSPO) expression) with repeated exposure to either MMC or METH. In Experiment 2, rats received repeated MMC (7.5, 15 or 30 mg/kg once a day for 10 days) and were examined for residual
Memory
, 2013
"... Differential correlates of autobiographical memory specificity to affective and selfdiscrepant cues ..."
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Differential correlates of autobiographical memory specificity to affective and selfdiscrepant cues
The AlignmentDistribution Graph
 In Proceedings of the Sixth Workshop on Languages and Compilers for Parallel Computing
, 1993
"... Implementing a dataparallel language such as Fortran 90 on a distributedmemory parallel computer requires distributing aggregate data objects (such as arrays) among the memory modules attached to the processors. The mapping of objects to the machine determines the amount of residual communicatio ..."
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Cited by 143 (3 self)
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Implementing a dataparallel language such as Fortran 90 on a distributedmemory parallel computer requires distributing aggregate data objects (such as arrays) among the memory modules attached to the processors. The mapping of objects to the machine determines the amount of residual
IN MEMORY OF
"... We examine, as a function of depth, the relationship between a tectonic regionalization and uppermantle shearwave heterogeneity represented by a recent seismic tomographic model. We perform Monte Carlo simulations that incorporate the spectral properties of both the regions and the seismic signal ..."
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We examine, as a function of depth, the relationship between a tectonic regionalization and uppermantle shearwave heterogeneity represented by a recent seismic tomographic model. We perform Monte Carlo simulations that incorporate the spectral properties of both the regions and the seismic signal. Our results indicate that ridges can be readily distinguished from older oceans to a depth of about 200 km. The corresponding platform and shield signature differs significantly (> 99 % confidence) from that under oceans and orogenic zones to at least 400 km depth. Results from analogous Monte Carlo simulations reveal that the earth's gravity variations correlate with surface tectonics no better than they would were the geoid (or gravity field) randomly oriented with respect to the surface. We estimate for the upper mantle a platform and shield signal of8 ±5 m and thus conclude that there is little contribution of platforms and shields to the gravity field, consistent with their keels having small density contrasts. We estimate an average value for
Results 1  10
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92,037