In this paper we present a new lossless image compression algorithm. To achieve the high compression speed we use a linear prediction, modified Golomb-Rice code family, and a very fast prediction error modeling method...
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In this paper we present a new lossless image compression algorithm. To achieve the high compression speed we use a linear prediction, modified Golomb-Rice code family, and a very fast prediction error modeling method. We compare the algorithm experimentally with others for medical and natural continuous tone grayscale images of depths of up to 16 bits. Its results are especially good for large images, for natural images of high bit depths, and for noisy images. The average compression speed on Intel Xeon 3.06 GHz CPU is 47 MB/s. For large images the speed is over 60 MB/s, i.e. the algorithm needs less than 50 CPU cycles per byte of image. Copyright (c) 2006 John Wiley & Sons, Ltd.
This work presents first simulation results substantiating a previously proposed conceptual model of computation in neocortical architecture [E. Korner, M.-O. Gewaltig, U. Korner, A. Richter, T. Rodemann, A model of c...
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This work presents first simulation results substantiating a previously proposed conceptual model of computation in neocortical architecture [E. Korner, M.-O. Gewaltig, U. Korner, A. Richter, T. Rodemann, A model of computation in neocortical architecture, Neural Networks 12 (1999) 989-1005]. This model gives a detailed functional interpretation of the six-layered columnar cortical architecture and related subcortical structures. It hypothesizes three interacting processing systems at each stage of the cortical hierarchy: The A-system (middle cortical layers) accomplishes fast bottom-up processing where the first spike wave traveling up the cortical hierarchy can activate a coarse initial hypothesis at each level. In the B-system (superficial layers) the initial hypothesis is refined by slower iterative processes involving feedback. Finally, the C-system. (deep layers) represents the local hypothesis of a macrocolumn which is fed back to the B-system of a lower level inducing expectations and predictions for the present and future input signals. These ideas are illustrated by an example implementation of the microcircuitry in a single cortical macrocolumn based on cell assemblies and associative memories. In a second step we have integrated our model at the level of V4 into a large scale implementation of the visual system involving several primary and higher visual cortical areas as well as parts of the hippocampal formation, and subcortical structures involved in generating eye saccades. With this model we can demonstrate object classification and the learning of new object representations. (c) 2006 Elsevier B.V. All rights reserved.
A lossy coding scheme is proposed for separate encoding and joint decoding of two correlated sequences. The algorithm simultaneously exploits the correlation between the sequences (using a binning-based quantization s...
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A lossy coding scheme is proposed for separate encoding and joint decoding of two correlated sequences. The algorithm simultaneously exploits the correlation between the sequences (using a binning-based quantization scheme) and that between the samples of each sequence (using linear prediction). Under the proposed coding regime, optimal prediction filter design fundamentally deviates from the traditional approach. More specifically, it is, in general, not optimal to employ first-order prediction for noisy observations of a first-order Markov source, even when the noise is negligibly small. Moreover, even if the prediction filter is constrained to be of degree 1, the optimal filter coefficient is different from the correlation coefficient of the Markov source. In the particular example treated in this paper, it is shown that optimal first- and second-order prediction respectively enjoy up to 0.9 dB and 1.15 dB improvement over the traditional approach.
In predictive coding of integers real-valued residuals are mapped to integers before encoding, leaving room for improvement by reducing the loss due to rounding. In this paper, we propose a new prefix coding scheme wh...
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In predictive coding of integers real-valued residuals are mapped to integers before encoding, leaving room for improvement by reducing the loss due to rounding. In this paper, we propose a new prefix coding scheme where actual integer values, instead of the residuals, are encoded using cosets, with real domain predictions as the side information. This novel coding scheme outperforms Golomb-based coding by reducing the rounding loss with similar computational and memory complexity.
Different cognitive functions recruit a number of different, often overlapping, areas of the brain. Theories in cognitive and computational neuroscience are beginning to take this kind of functional integration into a...
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Different cognitive functions recruit a number of different, often overlapping, areas of the brain. Theories in cognitive and computational neuroscience are beginning to take this kind of functional integration into account. The contributions to this special issue consider what functional integration tells us about various aspects of the mind such as perception, language, volition, agency, and reward. Here, I consider how and why functional integration may matter for the mind;I discuss a general theoretical framework, based on generative models, that may unify many of the debates surrounding functional integration and the mind;and I briefly introduce each of the contributions.
Neuronal responses to stimuli, measured electrophysiologically, unfold over several hundred milliseconds. Typically, they show characteristic waveforms with early and late components. It is thought that early or exoge...
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Neuronal responses to stimuli, measured electrophysiologically, unfold over several hundred milliseconds. Typically, they show characteristic waveforms with early and late components. It is thought that early or exogenous components reflect a perturbation of neuronal dynamics by sensory input bottom-up processing. Conversely, later, endogenous components have been ascribed to recurrent dynamics among hierarchically disposed cortical processing levels, top-down effects. Here, we show that evoked brain responses are generated by recurrent dynamics in cortical networks, and late components of event-related responses are mediated by backward connections. This evidence is furnished by dynamic causal modeling of mismatch responses, elicited in an oddball paradigm. We used the evidence for models with and without backward connections to assess their likelihood as a function of peristimulus time and show that backward connections are necessary to explain late components. Furthermore, we were able to quantify the contribution of backward connections to evoked responses and to source activity, again as a function of peristimulus time. These results link a generic feature of brain responses to changes in the sensorium and a key architectural component of functional anatomy;namely, backward connections are necessary for recurrent interactions among levels of cortical hierarchies. This is the theoretical cornerstone of most modern theories of perceptual inference and learning.
Motion is known to distort visual space, producing illusory mislocalizations for flashed objects. Previously, it has been shown that when a stationary bar is flashed in the proximity of a moving stimulus, the position...
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Motion is known to distort visual space, producing illusory mislocalizations for flashed objects. Previously, it has been shown that when a stationary bar is flashed in the proximity of a moving stimulus, the position of the flashed bar appears to be shifted in the direction of nearby motion. A model consisting of predictive projections from the sub-system that processes motion information onto the subsystem that processes position information can explain this illusory position shift of a stationary flashed bar in the direction of motion. Based on this model of motion-position interactions, we predict that the perceived position of a flashed stimulus should also be attracted towards a nearby moving stimulus. In the first experiment, observers judged the perceived vertical position of a flash with respect to two horizontally moving dots of unequal contrast. The results of this experiment were in agreement with our prediction of attraction towards the high contrast dot. We obtained similar findings when the moving dots were replaced by drifting gratings of unequal contrast. In control experiments, we found that neither attention nor eye movements can account for this illusion. We propose that the visual system uses predictive influences from the motion processing sub-system on the position processing sub-system to overcome the temporal limitations of the position processing system. Published by Elsevier Ltd.
Sensory information from the external world is inherently ambiguous, necessitating prior experience as a constraint on perception. Prolonged experience (adaptation) induces perception of ambiguous morph faces as a cat...
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Sensory information from the external world is inherently ambiguous, necessitating prior experience as a constraint on perception. Prolonged experience (adaptation) induces perception of ambiguous morph faces as a category different from the adapted category, suggesting sensitivity in underlying neural codes to differences between input and recent experience. Using magnetoencephalography, we investigated the neural dynamics of such experience-dependent visual coding by focusing on the timing of responses to morphs after facial expression adaptation. We show that evoked fields arising from the superior temporal sulcus (STS) reflect the degree to which a morph and adapted expression deviate. Furthermore, adaptation effects within STS predict the magnitude of behavioral aftereffects. These findings show that the STS codes expressions relative to recent experience rather than absolutely and may bias perception of expressions. One potential neural mechanism for the late timing of both effects appeals to hierarchical models that ascribe a central role to backward connections in mediating predictive codes.
This paper presents a fast lossless image compression method for space and satellite images. The method, which we call HIREW, is based on hierarchical interpolating prediction and adaptive Golomb-Rice coding, and achi...
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ISBN:
(纸本)9781424412112
This paper presents a fast lossless image compression method for space and satellite images. The method, which we call HIREW, is based on hierarchical interpolating prediction and adaptive Golomb-Rice coding, and achieves 7-35 times faster compression than existing methods such as JPEG2000 and JPEG-LS, at similar compression ratios. Additionally, unlike JPEG-LS, it supports additional features such as progressive decompression using resolution scaling. An implementation of this codec will be used in the Japan Aerospace Exploration Agency (JAXA)'s Venus Climate Orbiter mission (PLANET-C).
This paper describes about implementation of speech recognition on microcontroller. The microcontroller used in this system is ATMEL AT89C51RC microcontroller which is one of the MCS51 family microcontrollers. Speech ...
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ISBN:
(纸本)9781424413553
This paper describes about implementation of speech recognition on microcontroller. The microcontroller used in this system is ATMEL AT89C51RC microcontroller which is one of the MCS51 family microcontrollers. Speech recognition system is implemented to recognize the word used as the command for controlling movement of a wheelchair. There are two approaches used to recognize the speech signal. The first approach is Linear predictive coding combined with Euclidean Squared Distance. LPC is used as the feature extraction method and Euclidean squared Distance is used as the recognition method. The second approach is Hidden Markov Model, which is used to build reference model of the words and also used as the recognition method. Feature extraction method used in the second approach is a simple segmentation and centroid value. Both approaches work on time domain. Two DC motors are used as the actuator for driving the wheelchair. Both DC motors are controlled by ATMEL AT89C52 microcontroller and using a simple open loop control system. Experiments were done to analyze performance of both approaches. Each approach has advantages and disadvantages. The highest average recognition rate that can be achieved using LPC-Euclidean Squared Distance approach was 78.57%. The highest average recognition rate that can be achieved using HMM-Segmentation and Centroid approach was only 32.86%.
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