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IEEE International Conference on Signal Processing, Communications and Computing ICSPCC 2015

作者： Salah, Moataz M. Elrahman, Ashraf A. Egyptian Armed Forces Cairo Egypt King Khalid Univ Coll Comp Sci Comp Networks & Commun Engn Dept Abha Saudi Arabia

ISBN: (纸本)9781479989201

Relay communications channels have been shown to be used to achieve combined diversity and coding gain in wireless communications networks. To enhance the performance of relay network some cooperation and distributed coding schemes have been introduced. In relay networks signals transmitted from one terminal to another through a number of relays. Embedding the distributed turbo code (DTC) technique into the relay channels has been shown to approach the theoretical bound of the capacity of the wireless relay networks. In some applications, the availability of the power required at the source device to satisfy some level of quality at the destination device is not available, like in sensor networks, and in some other applications the power assigned for the source and relay devices are different. In this paper, for the distributed turbo code (DTC) in relay network, we consider a two hop relay network, which consists of one source device, one relay device and one destination device. So, in this paper, the power allocated to each component of the turbo code word, which are generated at both source device and at the relay device, has been investigated and conclusions are drawn for design purposes to enhance the performance of the distributed turbo code (DTC) in relay networks.

关键词： Turbo codes relay networks distributed coding Wireless Networks

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Research on Asymmetry Multi-terminal sources Audio coding Algorithm

Research on Asymmetry Multi-terminal sources Audio Coding Al...

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International Conference on Communication Software and Networks

作者： Jiang Yan Ning Gengxin Wei Gang Yang Yucun S China Univ Technol Sch Elect & Informat Engn Guangzhou Guangdong Peoples R China

ISBN: (纸本)9780769535227

Multi-terminal sources coding refers to separate lossy encoding and joint decoding of two or more correlated sources. Based on good output performance it can effectively reduce encoding complexity. With focus on the asymmetry case, This paper designs a asymmetry multi-terminal sources audio coding algorithm, then analyses and simulates it. The encouraging simulation results show multi-terminal sources audio coding is feasible, simple and can get higher acoustical effect.

关键词： Multi-terminal sources coding distributed coding Audio coding

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Stimulus number, duration and intensity encoding in randomly connected attractor networks with synaptic depression

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FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2013年第2013期7卷 59-59页

作者： Miller, Paul Brandeis Univ Volen Natl Ctr Complex Syst Waltham MA 02454 USA Brandeis Univ Dept Biol Waltham MA 02454 USA

Randomly connected recurrent networks of excitatory groups of neurons can possess a multitude of attractor states. When the internal excitatory synapses of these networks are depressing, the attractor states can be destabilized with increasing input. This leads to an itinerancy, where with either repeated transient stimuli, or increasing duration of a single stimulus, the network activity advances through sequences of attractor states. We find that the resulting network state, which persists beyond stimulus offset, can encode the number of stimuli presented via a distributed representation of neural activity with non-monotonic tuning curves for most neurons. Increased duration of a single stimulus is encoded via different distributed representations, so unlike an integrator, the network distinguishes separate successive presentations of a short stimulus from a single presentation of a longer stimulus with equal total duration. Moreover, different amplitudes of stimulus cause new, distinct activity patterns, such that changes in stimulus number, duration and amplitude can be distinguished from each other. These properties of the network depend on dynamic depressing synapses, as they disappear if synapses are static. Thus, short-term synaptic depression allows a network to store separately the different dynamic properties of a spatially constant stimulus.

关键词： short-term plasticity dynamic synapses attractor networks short-term memory distributed coding high-dimensional representation

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Systematic-bit-selection distributed with selective-relaying

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Journal of Beijing Institute of Technology 2014年第1期23卷 73-77页

作者： HOU Shu-juan LI Ling-yun QIN Xue-fang School of Information and Electronics Beijing Institute of Technology Beijing 100081 China

An improved distributed turbo coding （DTC） scheme, namely, systematic-bit-selection DTC, is proposed for a two-hop relay network implementing selective-relaying （SR）. In the scheme, source broadcasts a punctured turbo code in order to increase the successful decoding rate of relay. The relay forwards systematic-bit to the destination in case of successful cyclic redundancy check （CRC）. From the two versions of systematic-bit coming from relay and source respectively, the des- tination selects the one with higher signal-to-noise ratio （SNR） for turbo decoding. Simulation re- suits show the improved bit error rate （BER） performance of our scheme.

关键词： distributed coding relay network turbo coding selective-relaying

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Distinct ventral stream and prefrontal cortex representational dynamics during sustained conscious visual perception

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CELL REPORTS 2023年第7期42卷 112752页

作者： Vishne, Gal Gerber, Edden M. Knight, Robert T. Deouell, Leon Y. Hebrew Univ Jerusalem Edmond & Lily Safra Ctr Brain Sci IL-9190401 Jerusalem Israel Univ Calif Berkeley Helen Wills Neurosci Inst Berkeley CA 94720 USA Univ Calif Berkeley Dept Psychol Berkeley CA 94720 USA Hebrew Univ Jerusalem Dept Psychol IL-9190501 Jerusalem Israel

Instances of sustained stationary sensory input are ubiquitous. However, previous work focused almost exclusively on transient onset responses. This presents a critical challenge for neural theories of conscious-ness, which should account for the full temporal extent of experience. To address this question, we use intra-cranial recordings from ten human patients with epilepsy to view diverse images of multiple durations. We reveal that, in sensory regions, despite dramatic changes in activation magnitude, the distributed represen-tation of categories and exemplars remains sustained and stable. In contrast, in frontoparietal regions, we find transient content representation at stimulus onset. Our results highlight the connection between the anatomical and temporal correlates of experience. To the extent perception is sustained, it may rely on sen-sory representations and to the extent perception is discrete, centered on perceptual updating, it may rely on frontoparietal representations.

关键词： visual perception perceptual awareness neural correlates of consciousness time-consciousness discrete perception representation representational drift neural adaptation distributed coding Research topic(s)CP: Neuroscience

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How a Population-based Representation of Binocular Visual Signal Can Intrinsically Mediate Autonomous Learning of Vergence Control

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Procedia Computer Science 2012年 13卷 212-221页

作者： Agostino Gibaldi Andrea Canessa Manuela Chessa Fabio Solari Silvio P. Sabatini The Physical Structure of Perception and Computation Group DIBRIS -University of Genova -Via all’Opera Pia 11/A -16145 Genova Italy

Designing an active visual system, able to autonomously learn its behavior, implies to make the learning controller independent of an external signal (e.g. the error between the actual and the desired vergence angle) or of perceptual decisions about dispar–ity (e.g. from the response of a previously trained network). The proposed approach is based on a direct use of a computational substrate of modeled V1 complex cells that provide a distributed representation of binocular disparity information. The design strategies of the cortical-like architecture, including uniform coverage in feature space and divisive normalization mechanisms, allow the global energy of the population to effectively mediate the learning process towards the proper motor control. Since the learning controller is based on an intrinsic representation of the visual signal, it comes to overlap and coincide with the system that is learning the behaviour, thus closing at an inner cycle the perception-action loop necessary for learning. Experi–mental tests proved that the control architecture is both able to learn an effective vergence behavior, and to exploit it to ﬁxate static and moving visual targets.

关键词： Vergence control Autonomous learning distributed coding Binocular energy model

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distributed QUANTIZATION FOR COMPRESSED SENSING

DISTRIBUTED QUANTIZATION FOR COMPRESSED SENSING

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Amirpasha Shirazinia Saikat Chatterjee Mikael Skoglund Communication Theory Department ACCESS Linnaeus Centre KTH Royal Institute of Technology

ISBN: (纸本)9781479928941

We study distributed coding of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a distributed framework for realizing optimized quantizer that enables encoding CS measurements of correlated sparse sources followed by joint decoding at a fusion center. The optimality of VQ encoder-decoder pairs is addressed by minimizing the sum of mean-square errors between the sparse sources and their reconstruction vectors at the fusion center. We derive a lower-bound on the end-to-end performance of the studied distributed system, and propose a practical encoder-decoder design through an iterative algorithm.

关键词： Mean square error distributed coding end-to-end performance Fusion reactions FUSION fusion (melting) Vector quantization optimality Quantization COMPRESSED Iterative algorithms quantizer CONTAINMENT SPRAY carbon monosulfide Cesium

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UNIVERSAL ENcoding OF MULTISPECTRAL IMAGES

UNIVERSAL ENCODING OF MULTISPECTRAL IMAGES

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Diego Valsesia Petros T. Boufounos Polit??cnico di Torino

ISBN: (纸本)9781479999897

We propose a new method for low-complexity compression of multispectral images. We develop on a novel approach to coding signals with side information based on recent advances in compressed sensing and universal scalar quantization. Our approach can be interpreted as a variation of quantized compressed sensing, where the most significant bits are discarded at the encoder and recovered at the decoder from the side information. The image is reconstructed using weighted total variation minimization, incorporating side information in the weights while enforcing consistency with the recovered quantized coefficient values. Our experiments validate our approach and confirm the improvements in rate-distortion performance.

关键词： Compressed sensing distributed coding multispectral image compression universal quantization

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Non-iterative Content-Adaptive distributed Encoding Through ML Techniques

Non-iterative Content-Adaptive Distributed Encoding Through ...

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SMPTE Technical Conference

作者： Sriram Sethuraman Nithya V. S. Venkata Narayanababu Laveti D Ittiam Systems Pvt. Ltd. Bangalore India

ISBN: (纸本)9781510851771

distributed encoding is desired in content preparation workflows in the cloud to reduce turnaround times. Content-adaptive bit allocation at title, chunk, and even frame level, as opposed to using a fixed ladder of content-independent bit-rates and resolutions, have been proposed to achieve efficiencies in storage and delivery. Many of these methods tend to be iterative in nature and consume significant additional compute resources over 2-pass Variable bit-rate (VBR) encoders. With live use-cases attempting to use a set of distributed encoders to achieve higher bit-rate savings (both through use of higher compression presets and through content-adaptive bit allocation) and consistent quality, there is a need to limit the increase in computational complexity. In this paper, we propose a non-iterative codec-agnostic approach that employs machine learning techniques to perform consistent quality content-adaptive encoding within the constraints of a maximum bit-rate in a manner that makes it equally suitable for live and on-demand workflows. The method has the ability to take a target subjective rating level and allocate appropriate bits for each group of frames to achieve that. The proposed approach also anticipates automatic selection of the right resolution and frame-rate for a given representation within an ABR set, and content-specific encoding parameters to maximize the bit savings and/or visual quality. Test results are presented over a wide range of content types comparing the performance of the proposed approach against 2-pass VBR methods. Initial results indicate that the proposed approach can recover ~85% of the bit-savings possible with exhaustive techniques. The computational complexity of the proposed approach is only 15-20% of 2-pass VBR encoding.

关键词： Bit rate distributed coding variable Bit rate automatic selection complexity classes ENCODER Workflow Iterative

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A Noise-Invariant Sparse coding Model for Binary Input

A Noise-Invariant Sparse Coding Model for Binary Input

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International Conference on Intelligent Computing, Automation and Systems (ICICAS)

作者： Tao Zhou Yuanyuan Chen University of Electronic Science and Technology of China UESTC Chengdu China Sichuan University SCU Chengdu China

ISBN: (数字)9781728161068

ISBN: (纸本)9781728161075

A sparse distributed coding model that is consistent with the basic properties of the primary visual cortex is introduced. The binary input can be sparsely represented after a learning stage. The results of the sparse distributed coding have only a few nonzero coefficients to represent the input. In addition, it can also get the relative noise-robust representation. Firstly, a set of basic binary images or basic vectors can be found from the training data. Secondly, any binary input with the same dimension can be described as a linear combination of the basic vectors. According to the experimental results, the proposed coding model not only.

关键词： image coding image representation learning (artificial intelligence) vectors image representation image coding binary input distributed coding Cloning Vectors Striate Cortex Linear Combination Sparse coding Alkali Basic language

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