In this paper, we present a new family of fountain codes which overcome adversarial errors. That is, we consider the possibility that some portion of the arriving packets of a rateless erasure code are corrupted in an...
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In this paper, we present a new family of fountain codes which overcome adversarial errors. That is, we consider the possibility that some portion of the arriving packets of a rateless erasure code are corrupted in an undetectable fashion. In practice, the corrupted packets may be attributed to a portion of the communication paths which are controlled by an adversary or to a portion of the sources that are malicious. The presented codes resemble and extend rateless codes. Yet, their benefits over existing coding schemes are manifold. First, to overcome the corrupted packets, our codes use information theoretic techniques, rather than cryptographic primitives. Thus, no secret channel between the senders and the receivers is required. Second, the encoders in the suggested scheme are oblivious to the strength of the adversary, yet perform as if its strength was known in advance. Third, the sparse structure of the codes facilitates efficient decoding. Finally, the codes easily fit a decentralized scenario with several sources, when no communication between the sources is allowed. We present both exhaustive as well as efficient decoding rules. Beyond the obvious use as a rateless codes, our codes have important applications in distributed computing.
We describe the results of quantitative information theoretic analyses of neural encoding, particularly in the primate visual, olfactory, taste, hippocampal, and orbitofrontal cortex. Most of the information turns out...
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We describe the results of quantitative information theoretic analyses of neural encoding, particularly in the primate visual, olfactory, taste, hippocampal, and orbitofrontal cortex. Most of the information turns out to be encoded by the firing rates of the neurons, that is by the number of spikes in a short time window. This has been shown to be a robust code, for the firing rate representations of different neurons are close to independent for small populations of neurons. Moreover, the information can be read fast from such encoding, in as little as 20 ms. In quantitative information theoretic studies, only a little additional information is available in temporal encoding involving stimulus-dependent synchronization of different neurons, or the timing of spikes within the spike train of a single neuron. Feature binding appears to be solved by feature combination neurons rather than by temporal synchrony. The code is sparse distributed, with the spike firing rate distributions close to exponential or gamma. A feature of the code is that it can be read by neurons that take a synaptically weighted sum of their inputs. This dot product decoding is biologically plausible. Understanding the neural code is fundamental to understanding not only how the cortex represents, but also processes, information. (C) 2011 Elsevier Ltd. All rights reserved.
Although previous studies have implicated a diverse set of brain regions in reward-related decision making, it is not yet known which of these regions contain information that directly reflects a decision. Here, we me...
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Although previous studies have implicated a diverse set of brain regions in reward-related decision making, it is not yet known which of these regions contain information that directly reflects a decision. Here, we measured brain activity using functional MRI in a group of subjects while they performed a simple reward-based decision-making task: probabilistic reversal-learning. We recorded brain activity from nine distinct regions of interest previously implicated in decision making and separated out local spatially distributed signals in each region from global differences in signal. Using a multivariate analysis approach, we determined the extent to which global and local signals could be used to decode subjects' subsequent behavioral choice, based on their brain activity on the preceding trial. We found that subjects' decisions could be decoded to a high level of accuracy on the basis of both local and global signals even before they were required to make a choice, and even before they knew which physical action would be required. Furthermore, the combined signals from three specific brain areas (anterior cingulate cortex, medial prefrontal cortex, and ventral striatum) were found to provide all of the information sufficient to decode subjects' decisions out of all of the regions we studied. These findings implicate a specific network of regions in encoding information relevant to subsequent behavioral choice.
Prosopagnosia is a brain disorder causing the inability to recognize faces. Previous studies have shown that the lesions producing the disorder can occur in diverse areas of the brain. However, the most common region ...
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ISBN:
(纸本)9781424496365
Prosopagnosia is a brain disorder causing the inability to recognize faces. Previous studies have shown that the lesions producing the disorder can occur in diverse areas of the brain. However, the most common region is the "fusiform face area" (FFA). In order to model the basic properties of prosopagnosia two networks have been used concurrently: the Feature Extracting Bidirectional Associative Memory (FEBAM-SOM) and the Bidirectional Associative Memory (BAM). The FEBAM-SOM creates a 2D topological map from correlated inputs through the categorization of various exemplars (faces and various objects). This model has the advantage of using a sparse representation which encompass both localist and distributed encoding. This process simulates the FFA in the brain by exhibiting attractor-like behavior for the categorization of all faces. Once the faces have been learned, the BAM model associates specific faces (and objects) to their corresponding semantic labels. Simulations were performed to study the recall performance in function of the size of the lesions. Results show that the recall performance of the names associated with faces decrease with the size of lesion without affecting the performance of the objects.
Applied research of an automated method to quickly emerge better encoding profiles, using Genetic Algorithms with many source video samples to converge to the specified limits of processing time, video quality and fil...
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ISBN:
(纸本)9788576691990
Applied research of an automated method to quickly emerge better encoding profiles, using Genetic Algorithms with many source video samples to converge to the specified limits of processing time, video quality and file size.
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