The Experts below are selected from a list of 249 Experts worldwide ranked by ideXlab platform
Sundar B. Rajan - One of the best experts on this subject based on the ideXlab platform.
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Index Coded PSK Modulation for Prioritized Receivers
IEEE Transactions on Vehicular Technology, 2017Co-Authors: Divya Usha Sudhakaran, Sundar B. RajanAbstract:A noisy index coding problem (ICP) over additive white Gaussian noise (AWGN) and Rayleigh fading channels is studied. First, a single-input single-output AWGN broadcast channel is considered. For a chosen index code and an Arbitrary Mapping (of broadcast vectors to phase-shift keying (PSK) signal points), a decision rule for the maximum-likelihood (ML) decoder is derived. The message error performance of a receiver at high signal-to-noise ratio (SNR) is characterized by a parameter called PSK-index coding gain (PSK-ICG). The PSK-ICG of a receiver is determined by a metric called minimum inter-set distance. For a given ICP with an order of priority among the receivers, and a chosen 2N-PSK constellation, an algorithm to find (index code, Mapping) pairs, each of which gives the best performance in terms of PSK-ICG of the receivers, is proposed. No other pair of index code (of length N with 2N broadcast vectors) and Mapping can give a better PSK-ICG for the highest priority receiver. Also, given that the highest priority receiver achieves its best performance, the next highest priority receiver achieves its maximum gain possible and so on in the specified order of priority. Next, the noisy ICP over a multiple-input multiple-output (MIMO) Rayleigh fading channel is considered. The receivers are equipped with a single antenna and a server with two antennas. To obtain the diversity gain along with the coding gain, a MIMO scheme that employs space-time coding along with index coded PSK modulation is proposed. For a chosen index code, an Arbitrary Mapping (of broadcast vectors to PSK signal points), and a 2 × 1 MIMO system employing Alamouti code, we derive a decision rule for the ML decoding. We show that for the best coding gain at high SNR, the Mapping must maximize the minimum inter-set distance.
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Alamouti-Index-Coded PSK Modulation for Priority Ordered Receivers
GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017Co-Authors: Divya Usha Sudhakaran, Sundar B. RajanAbstract:Noisy index coding problem over a Rayleigh fading channel is studied. The receivers are assumed to be priority ordered with each of them equipped with single antenna and the server with two antennas. To obtain diversity gain along with coding gain, a multiple-input multiple-output (MIMO) scheme which employs space time coding along with index coded PSK modulation, is proposed. For a chosen index code, an Arbitrary Mapping (of broadcast vectors to PSK signal points) and a 2x1 MIMO system employing Alamouti code, a decision rule for the maximum likelihood (ML) decoding is derived. It is shown that, at very high SNR, the message error performance of the receiver employing ML decoder, depends on the metric called minimum inter-set distance, and for the best coding gain at high SNR, the Mapping must maximize the minimum inter-set distance.
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Maximum Likelihood Decoder for Index Coded PSK Modulation for Priority Ordered Receivers
2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 2017Co-Authors: Divya Usha Sudhakaran, Sundar B. RajanAbstract:Index coded PSK modulation over an AWGN broadcast channel, for a given index coding problem (ICP) is studied. For a chosen index code and an Arbitrary Mapping (of broadcast vectors to PSK signal points), a decision rule for the maximum likelihood (ML) decoder is derived. The message error performance of a receiver at high SNR is characterized by a parameter called PSK-index coding gain (PSK-ICG). The PSKICG of a receiver is determined by a metric called minimum interset distance. For a given ICP with an order of priority among the receivers, and a chosen 2N-PSK constellation an algorithm to find (index code, Mapping) pairs, each of which gives the best performance in terms of PSK-ICG of the receivers, is proposed. No other pair of index code (of length N with 2N broadcast vectors) and Mapping can give a better PSK-ICG for the highest priority receiver. Also, given that the highest priority receiver achieves its best performance, the next highest priority receiver achieves its maximum gain possible and so on in the specified order of priority.
Igor N. Aizenberg - One of the best experts on this subject based on the ideXlab platform.
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Classification of the images of gene expression patterns using neural networks based on multivalued neurons with the minimal number of inputs
electronic imaging, 2002Co-Authors: Igor N. Aizenberg, Ekaterina Myasnikova, Maria Samsonova, Constantine Butakoff, John ReinitzAbstract:Multi-valued neurons (MVN) are the neural processing elements with complex-valued weights and high functionality. It is possible to implement an Arbitrary Mapping described by partial-defined multiple-valued function on the single MVN. The MVN-based neural networks are applied to temporal classification of images of gene expression patterns, obtained by confocal scanning microscopy. The classification results confirmed the efficiency of this method for image recognition. It was shown that frequency domain of the representation of gene expression images is highly effective for their description.
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Fuzzy Days - Application of the Neural Networks Based on Multi-valued Neurons to Classification of the Images of Gene Expression Patterns
Computational Intelligence. Theory and Applications, 2001Co-Authors: Igor N. Aizenberg, Ekaterina Myasnikova, Maria Samsonova, John ReinitzAbstract:Multi-valued neurons (MVN) are the neural processing elements with complex-valued weights and high functionality. It is possible to implement an Arbitrary Mapping described by partial-defined multiple-valued function on the single MVN. The MVN-based neural networks are applied to temporal classification of images of gene expression patterns, obtained by confocal scanning microscopy. The classification results confirmed the efficiency of this method for image recognition. It was shown that frequency domain of the representation of images is highly effective for their description.
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Fuzzy Days - Multi-valued and Universal Binary Neurons: New Applications in Intelligent Image Processing
Computational Intelligence. Theory and Applications, 2001Co-Authors: Igor N. AizenbergAbstract:Multi-valued neurons (MVN) and universal binary neurons (UBN) are neural elements with complex-valued weights and high functionality. It is possible to implement the Arbitrary Mapping described by partially defined multiple-valued function on the single MVN and the Arbitrary Mapping described by Boolean function (which may not be threshold) on the single UBN. In this paper we consider some applications carried out using these wonderful features of MVN and UBN. Conception of cellular neural networks based on MVN and UBN becomes a base for nonlinear cellular neural filtering. Application of the corresponding filters for edge detection and solving of the super-resolution problem are considered in the paper.
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IWANN (2) - Classification of the Images of Gene Expression Patterns Using Neural Networks Based on Multi-valued Neurons
Bio-Inspired Applications of Connectionism, 2001Co-Authors: Igor N. Aizenberg, Ekaterina Myasnikova, Maria SamsonovaAbstract:Multi-valued neurons (MVN) are the neural processing elements with complex-valued weights and high functionality. It is possible to implement an Arbitrary Mapping described by partial-defined multiple-valued function on the single MVN. The MVN-based neural networks are applied to temporal classification of images of gene expression patterns, obtained by confocal scanning microscopy.
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Image processing using cellular neural networks based on multi-valued and universal binary neurons
Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501), 2000Co-Authors: Igor N. Aizenberg, N. Aizenberg, T. Bregin, C. Butakov, E. FarberovAbstract:Multi-valued neurons (MVNs) and universal binary neurons (UBNs) are neural processing elements with complex-valued weights and high functionality. It is possible to implement an Arbitrary Mapping described by a partially-defined multiple-valued function on a single MVN, and an Arbitrary Mapping described by a partially-defined or fully-defined Boolean function (which does not have to be a threshold function) on a single UBN. Rapidly-converging learning algorithms exist for both types of neurons. Such features of MVNs and UBNs may be used to solve different kinds of problems. One of the most successful applications of MVNs and UBNs is their use as basic neurons in cellular neural networks (CNNs) to solve image processing and image analysis problems.
Divya Usha Sudhakaran - One of the best experts on this subject based on the ideXlab platform.
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Index Coded PSK Modulation for Prioritized Receivers
IEEE Transactions on Vehicular Technology, 2017Co-Authors: Divya Usha Sudhakaran, B. Sundar RajanAbstract:A noisy index coding problem (ICP) over additive white Gaussian noise (AWGN) and Rayleigh fading channels is studied. First, a single-input single-output AWGN broadcast channel is considered. For a chosen index code and an Arbitrary Mapping (of broadcast vectors to phase-shift keying (PSK) signal points), a decision rule for the maximum-likelihood (ML) decoder is derived. The message error performance of a receiver at high signal-to-noise ratio (SNR) is characterized by a parameter called PSK-index coding gain (PSK-ICG) . The PSK-ICG of a receiver is determined by a metric called minimum inter-set distance . For a given ICP with an order of priority among the receivers, and a chosen $2^N$ -PSK constellation, an algorithm to find (index code, Mapping) pairs, each of which gives the best performance in terms of PSK-ICG of the receivers, is proposed. No other pair of index code (of length $N$ with $2^N$ broadcast vectors) and Mapping can give a better PSK-ICG for the highest priority receiver. Also, given that the highest priority receiver achieves its best performance, the next highest priority receiver achieves its maximum gain possible and so on in the specified order of priority. Next, the noisy ICP over a multiple-input multiple-output (MIMO) Rayleigh fading channel is considered. The receivers are equipped with a single antenna and a server with two antennas. To obtain the diversity gain along with the coding gain, a MIMO scheme that employs space-time coding along with index coded PSK modulation is proposed. For a chosen index code, an Arbitrary Mapping (of broadcast vectors to PSK signal points), and a $2 \times 1$ MIMO system employing Alamouti code, we derive a decision rule for the ML decoding. We show that for the best coding gain at high SNR, the Mapping must maximize the minimum inter-set distance.
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GLOBECOM - Alamouti-Index-Coded PSK Modulation for Priority Ordered Receivers
GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017Co-Authors: Divya Usha Sudhakaran, B. Sundar RajanAbstract:Noisy index coding problem over a Rayleigh fading channel is studied. The receivers are assumed to be priority ordered with each of them equipped with single antenna and the server with two antennas. To obtain diversity gain along with coding gain, a multiple-input multiple-output (MIMO) scheme which employs space time coding along with index coded PSK modulation, is proposed. For a chosen index code, an Arbitrary Mapping (of broadcast vectors to PSK signal points) and a 2x1 MIMO system employing Alamouti code, a decision rule for the maximum likelihood (ML) decoding is derived. It is shown that, at very high SNR, the message error performance of the receiver employing ML decoder, depends on the metric called minimum inter-set distance, and for the best coding gain at high SNR, the Mapping must maximize the minimum inter-set distance.
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Index Coded PSK Modulation for Prioritized Receivers
IEEE Transactions on Vehicular Technology, 2017Co-Authors: Divya Usha Sudhakaran, Sundar B. RajanAbstract:A noisy index coding problem (ICP) over additive white Gaussian noise (AWGN) and Rayleigh fading channels is studied. First, a single-input single-output AWGN broadcast channel is considered. For a chosen index code and an Arbitrary Mapping (of broadcast vectors to phase-shift keying (PSK) signal points), a decision rule for the maximum-likelihood (ML) decoder is derived. The message error performance of a receiver at high signal-to-noise ratio (SNR) is characterized by a parameter called PSK-index coding gain (PSK-ICG). The PSK-ICG of a receiver is determined by a metric called minimum inter-set distance. For a given ICP with an order of priority among the receivers, and a chosen 2N-PSK constellation, an algorithm to find (index code, Mapping) pairs, each of which gives the best performance in terms of PSK-ICG of the receivers, is proposed. No other pair of index code (of length N with 2N broadcast vectors) and Mapping can give a better PSK-ICG for the highest priority receiver. Also, given that the highest priority receiver achieves its best performance, the next highest priority receiver achieves its maximum gain possible and so on in the specified order of priority. Next, the noisy ICP over a multiple-input multiple-output (MIMO) Rayleigh fading channel is considered. The receivers are equipped with a single antenna and a server with two antennas. To obtain the diversity gain along with the coding gain, a MIMO scheme that employs space-time coding along with index coded PSK modulation is proposed. For a chosen index code, an Arbitrary Mapping (of broadcast vectors to PSK signal points), and a 2 × 1 MIMO system employing Alamouti code, we derive a decision rule for the ML decoding. We show that for the best coding gain at high SNR, the Mapping must maximize the minimum inter-set distance.
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Alamouti-Index-Coded PSK Modulation for Priority Ordered Receivers
GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017Co-Authors: Divya Usha Sudhakaran, Sundar B. RajanAbstract:Noisy index coding problem over a Rayleigh fading channel is studied. The receivers are assumed to be priority ordered with each of them equipped with single antenna and the server with two antennas. To obtain diversity gain along with coding gain, a multiple-input multiple-output (MIMO) scheme which employs space time coding along with index coded PSK modulation, is proposed. For a chosen index code, an Arbitrary Mapping (of broadcast vectors to PSK signal points) and a 2x1 MIMO system employing Alamouti code, a decision rule for the maximum likelihood (ML) decoding is derived. It is shown that, at very high SNR, the message error performance of the receiver employing ML decoder, depends on the metric called minimum inter-set distance, and for the best coding gain at high SNR, the Mapping must maximize the minimum inter-set distance.
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Maximum Likelihood Decoder for Index Coded PSK Modulation for Priority Ordered Receivers
2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 2017Co-Authors: Divya Usha Sudhakaran, Sundar B. RajanAbstract:Index coded PSK modulation over an AWGN broadcast channel, for a given index coding problem (ICP) is studied. For a chosen index code and an Arbitrary Mapping (of broadcast vectors to PSK signal points), a decision rule for the maximum likelihood (ML) decoder is derived. The message error performance of a receiver at high SNR is characterized by a parameter called PSK-index coding gain (PSK-ICG). The PSKICG of a receiver is determined by a metric called minimum interset distance. For a given ICP with an order of priority among the receivers, and a chosen 2N-PSK constellation an algorithm to find (index code, Mapping) pairs, each of which gives the best performance in terms of PSK-ICG of the receivers, is proposed. No other pair of index code (of length N with 2N broadcast vectors) and Mapping can give a better PSK-ICG for the highest priority receiver. Also, given that the highest priority receiver achieves its best performance, the next highest priority receiver achieves its maximum gain possible and so on in the specified order of priority.
Fernando Marmolejoramos - One of the best experts on this subject based on the ideXlab platform.
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age of acquisition effects on word processing for chinese native learners english erp evidence for the Arbitrary Mapping hypothesis
Frontiers in Psychology, 2017Co-Authors: Fernando MarmolejoramosAbstract:The present study aimed at distinguishing processing of early learned L2 words from late ones for Chinese natives who learn English as a foreign language. Specifically, we examined whether the age of acquisition (AoA) effect arose during the Arbitrary Mapping from conceptual knowledge onto linguistic units. The behavior and ERP data were collected when 28 Chinese-English bilinguals were asked to perform semantic relatedness judgment on word pairs, which represented three stages of word learning (i.e., primary school, junior and senior high schools). A 3 (AoA: early vs. intermediate vs. late) × 2 (regularity: regular vs. irregular) × 2 (semantic relatedness: related vs. unrelated) × 2 (hemisphere: left vs. right) × 3 (brain area: anterior vs. central vs. posterior) within-subjects design was adopted. Results from the analysis of N100 and N400 amplitudes showed that early learned words had an advantage in processing accuracy and speed; there is a tendency that the age of acquisition (AoA) effect was more pronounced for irregular word pairs and in the semantic related condition. More important, ERP results showed early acquired words induced larger N100 amplitudes for early AoA words in the parietal area and more negative-going N400 than late acquire words in the frontal and central regions. The results indicate the locus of the AoA effect might derive from the Arbitrary Mapping between word forms and semantic concepts, and early acquired words have more semantic interconnections than late acquired words.
Panagiotis Artemiadis - One of the best experts on this subject based on the ideXlab platform.
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Learning efficient control of robots using myoelectric interfaces
2014 IEEE International Conference on Robotics and Automation (ICRA), 2014Co-Authors: Mark Ison, Chris Wilson Antuvan, Panagiotis ArtemiadisAbstract:Myoelectric controlled interfaces are a vital component for advancing applications in prostheses, exoskeletons, and robot teleoperation. Current methods search for optimal neural decoders for enhanced initial user performance. However, recent studies demonstrate learning an inverse model of abstract decoders to improve performance over time. This paper proposes a paradigm shift on myoelectric interfaces by embedding the human as controller of a system and allowing the human to learn how to control it via control tasks with similar Mapping functions. The method is tested using two different control tasks and four different abstract Mappings of upper limb myoelectric signals to control actions for those tasks. The results confirm that all subjects are able to learn the Mappings and improve performance efficiency over time. A cross-trial evaluation reveals a significant learning transfer when a new control task is presented using the same Mapping as a previous task, resulting in enhanced initial performance with the new task. Comparison of EMG signal evolution across subjects indicates a significant population-wide muscle synergy development that results from learning and implementing the inverse model of the Mapping function to complete the tasks. This suggests that efficient performance may be achieved by learning a constant, Arbitrary Mapping function applied to multiple control tasks rather than dynamic subject- or task-specific functions. Moreover, this method can be used for the neural control of any device or robot, without restricting them to anthropomorphic or human-related counterparts.
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Embedded Human Control of Robots Using Myoelectric Interfaces
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2014Co-Authors: Chris Wilson Antuvan, Mark Ison, Panagiotis ArtemiadisAbstract:Myoelectric controlled interfaces have become a research interest for use in advanced prostheses, exoskeletons, and robot teleoperation. Current research focuses on improving a user's initial performance, either by training a decoding function for a specific user or implementing “intuitive” Mapping functions as decoders. However, both approaches are limiting, with the former being subject specific, and the latter task specific. This paper proposes a paradigm shift on myoelectric interfaces by embedding the human as controller of the system to be operated. Using abstract Mapping functions between myoelectric activity and control actions for a task, this study shows that human subjects are able to control an artificial system with increasing efficiency by just learning how to control it. The method efficacy is tested by using two different control tasks and four different abstract Mappings relating upper limb muscle activity to control actions for those tasks. The results show that all subjects were able to learn the Mappings and improve their performance over time. More interestingly, a chronological evaluation across trials reveals that the learning curves transfer across subsequent trials having the same Mapping, independent of the tasks to be executed. This implies that new muscle synergies are developed and refined relative to the Mapping used by the control task, suggesting that maximal performance may be achieved by learning a constant, Arbitrary Mapping function rather than dynamic subject- or task-specific functions. Moreover, the results indicate that the method may extend to the neural control of any device or robot, without limitations for anthropomorphism or human-related counterparts.
