The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Abhijit Chatterjee - One of the best experts on this subject based on the ideXlab platform.
-
Automatic Test Stimulus Generation for Diagnosis of RF Transceivers Using Model Parameter Estimation
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2015Co-Authors: Aritra Banerjee, Abhijit ChatterjeeAbstract:In this brief, an optimized Test Stimulus generation technique is proposed for model parameter computation-based diagnosis and Testing, which can provide a very compact deterministic Test signal and results in significant reduction in Test time. The proposed Test Stimulus generation algorithm maximizes the accuracy with which a nonlinear solver can determine RF transceiver model parameters from raw downconverted Test response data. The simulation results show that using optimized Test signals, a comprehensive range of model parameters can be computed accurately using a single data acquisition. Data from experiments performed on a hardware prototype are shown to validate the proposed methodology.
-
Automatic Test Stimulus generation for accurate diagnosis of RF systems using transient response signatures
29th VLSI Test Symposium, 2011Co-Authors: Aritra Banerjee, Shyam Kumar Devarakond, Abhijit ChatterjeeAbstract:Low cost diagnosis of RF systems has become an important problem due to increased process variability effects on the performance of RF devices and the need to ramp-up RF IC yield rapidly. In the recent past, there has been work on diagnosing RF device model parameters from random “frequency-rich” Test Stimulus. In this paper, we develop a novel Test Stimulus generation approach which produces a compact, deterministic Test Stimulus in such a way that the RF DUT model parameters can be computed directly from the DUT response (called the DUT signature). This is achieved through use of a non-linear solver that adjusts the DUT model parameters iteratively until the model response to the applied Test matches the observed DUT Test response signature. It is shown that a small set of optimized tones in the frequency domain or an optimized transient waveform in the time domain can be used as Test Stimulus. It is shown how the use of embedded sensors in the RF design can expedite model parameter diagnosis. The practicality and accuracy of the proposed diagnosis approach is shown through simulations and hardware measurements.
-
VTS - Automatic Test Stimulus generation for accurate diagnosis of RF systems using transient response signatures
29th VLSI Test Symposium, 2011Co-Authors: Aritra Banerjee, Shyam Kumar Devarakond, Abhijit ChatterjeeAbstract:Low cost diagnosis of RF systems has become an important problem due to increased process variability effects on the performance of RF devices and the need to ramp-up RF IC yield rapidly. In the recent past, there has been work on diagnosing RF device model parameters from random “frequency-rich” Test Stimulus. In this paper, we develop a novel Test Stimulus generation approach which produces a compact, deterministic Test Stimulus in such a way that the RF DUT model parameters can be computed directly from the DUT response (called the DUT signature). This is achieved through use of a non-linear solver that adjusts the DUT model parameters iteratively until the model response to the applied Test matches the observed DUT Test response signature. It is shown that a small set of optimized tones in the frequency domain or an optimized transient waveform in the time domain can be used as Test Stimulus. It is shown how the use of embedded sensors in the RF design can expedite model parameter diagnosis. The practicality and accuracy of the proposed diagnosis approach is shown through simulations and hardware measurements.
-
VLSI Design - Optimized Multitone Test Stimulus Driven Diagnosis of RF Transceivers Using Model Parameter Estimation
2011 24th Internatioal Conference on VLSI Design, 2011Co-Authors: Aritra Banerjee, Abhijit Chatterjee, Vishwanath Natarajan, Ganesh Srinivasan, S. BhattacharyaAbstract:Test time and Test complexity reduction has become a critical challenge in modern RF Testing. Prior “alternative” Test methods have achieved fast Testing at the cost of using supervised learning algorithms that require “training”. In contrast, behavioral model parameter estimation based Test methods require the use of accurate models but no “training” is necessary, reducing Test deployment costs. In this work, a new Test generation approach is proposed that allows behavioral model parameter estimation to be performed from a single optimized OFDM data frame. A genetic multi-tone Test Stimulus optimization algorithm is developed to maximize the accuracy with which a nonlinear solver can determine RF transceiver model parameters from raw downconverted Test response data. The transceiver model proposed is the most comprehensive to date and includes AM-PM distortion and 5th order nonlinearity effects. Simulation results show that using the optimized multitone Test Stimulus, all the model parameters can be computed accurately using a single data acquisition (4X-5X faster than prior parameter estimation techniques and comparable to alternative Test times). Data from an experiment performed on a hardware prototype validates the proposed concept.
-
Optimized Multitone Test Stimulus Driven Diagnosis of RF Transceivers Using Model Parameter Estimation
2011 24th Internatioal Conference on VLSI Design, 2011Co-Authors: Aritra Banerjee, Abhijit Chatterjee, Vishwanath Natarajan, Ganesh Srinivasan, Soumendu BhattacharyaAbstract:Test time and Test complexity reduction has become a critical challenge in modern RF Testing. Prior “alternative” Test methods have achieved fast Testing at the cost of using supervised learning algorithms that require “training”. In contrast, behavioral model parameter estimation based Test methods require the use of accurate models but no “training” is necessary, reducing Test deployment costs. In this work, a new Test generation approach is proposed that allows behavioral model parameter estimation to be performed from a single optimized OFDM data frame. A genetic multi-tone Test Stimulus optimization algorithm is developed to maximize the accuracy with which a nonlinear solver can determine RF transceiver model parameters from raw downconverted Test response data. The transceiver model proposed is the most comprehensive to date and includes AM-PM distortion and 5th order nonlinearity effects. Simulation results show that using the optimized multitone Test Stimulus, all the model parameters can be computed accurately using a single data acquisition (4X-5X faster than prior parameter estimation techniques and comparable to alternative Test times). Data from an experiment performed on a hardware prototype validates the proposed concept.
Aritra Banerjee - One of the best experts on this subject based on the ideXlab platform.
-
Automatic Test Stimulus Generation for Diagnosis of RF Transceivers Using Model Parameter Estimation
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2015Co-Authors: Aritra Banerjee, Abhijit ChatterjeeAbstract:In this brief, an optimized Test Stimulus generation technique is proposed for model parameter computation-based diagnosis and Testing, which can provide a very compact deterministic Test signal and results in significant reduction in Test time. The proposed Test Stimulus generation algorithm maximizes the accuracy with which a nonlinear solver can determine RF transceiver model parameters from raw downconverted Test response data. The simulation results show that using optimized Test signals, a comprehensive range of model parameters can be computed accurately using a single data acquisition. Data from experiments performed on a hardware prototype are shown to validate the proposed methodology.
-
Automatic Test Stimulus generation for accurate diagnosis of RF systems using transient response signatures
29th VLSI Test Symposium, 2011Co-Authors: Aritra Banerjee, Shyam Kumar Devarakond, Abhijit ChatterjeeAbstract:Low cost diagnosis of RF systems has become an important problem due to increased process variability effects on the performance of RF devices and the need to ramp-up RF IC yield rapidly. In the recent past, there has been work on diagnosing RF device model parameters from random “frequency-rich” Test Stimulus. In this paper, we develop a novel Test Stimulus generation approach which produces a compact, deterministic Test Stimulus in such a way that the RF DUT model parameters can be computed directly from the DUT response (called the DUT signature). This is achieved through use of a non-linear solver that adjusts the DUT model parameters iteratively until the model response to the applied Test matches the observed DUT Test response signature. It is shown that a small set of optimized tones in the frequency domain or an optimized transient waveform in the time domain can be used as Test Stimulus. It is shown how the use of embedded sensors in the RF design can expedite model parameter diagnosis. The practicality and accuracy of the proposed diagnosis approach is shown through simulations and hardware measurements.
-
VTS - Automatic Test Stimulus generation for accurate diagnosis of RF systems using transient response signatures
29th VLSI Test Symposium, 2011Co-Authors: Aritra Banerjee, Shyam Kumar Devarakond, Abhijit ChatterjeeAbstract:Low cost diagnosis of RF systems has become an important problem due to increased process variability effects on the performance of RF devices and the need to ramp-up RF IC yield rapidly. In the recent past, there has been work on diagnosing RF device model parameters from random “frequency-rich” Test Stimulus. In this paper, we develop a novel Test Stimulus generation approach which produces a compact, deterministic Test Stimulus in such a way that the RF DUT model parameters can be computed directly from the DUT response (called the DUT signature). This is achieved through use of a non-linear solver that adjusts the DUT model parameters iteratively until the model response to the applied Test matches the observed DUT Test response signature. It is shown that a small set of optimized tones in the frequency domain or an optimized transient waveform in the time domain can be used as Test Stimulus. It is shown how the use of embedded sensors in the RF design can expedite model parameter diagnosis. The practicality and accuracy of the proposed diagnosis approach is shown through simulations and hardware measurements.
-
VLSI Design - Optimized Multitone Test Stimulus Driven Diagnosis of RF Transceivers Using Model Parameter Estimation
2011 24th Internatioal Conference on VLSI Design, 2011Co-Authors: Aritra Banerjee, Abhijit Chatterjee, Vishwanath Natarajan, Ganesh Srinivasan, S. BhattacharyaAbstract:Test time and Test complexity reduction has become a critical challenge in modern RF Testing. Prior “alternative” Test methods have achieved fast Testing at the cost of using supervised learning algorithms that require “training”. In contrast, behavioral model parameter estimation based Test methods require the use of accurate models but no “training” is necessary, reducing Test deployment costs. In this work, a new Test generation approach is proposed that allows behavioral model parameter estimation to be performed from a single optimized OFDM data frame. A genetic multi-tone Test Stimulus optimization algorithm is developed to maximize the accuracy with which a nonlinear solver can determine RF transceiver model parameters from raw downconverted Test response data. The transceiver model proposed is the most comprehensive to date and includes AM-PM distortion and 5th order nonlinearity effects. Simulation results show that using the optimized multitone Test Stimulus, all the model parameters can be computed accurately using a single data acquisition (4X-5X faster than prior parameter estimation techniques and comparable to alternative Test times). Data from an experiment performed on a hardware prototype validates the proposed concept.
-
Optimized Multitone Test Stimulus Driven Diagnosis of RF Transceivers Using Model Parameter Estimation
2011 24th Internatioal Conference on VLSI Design, 2011Co-Authors: Aritra Banerjee, Abhijit Chatterjee, Vishwanath Natarajan, Ganesh Srinivasan, Soumendu BhattacharyaAbstract:Test time and Test complexity reduction has become a critical challenge in modern RF Testing. Prior “alternative” Test methods have achieved fast Testing at the cost of using supervised learning algorithms that require “training”. In contrast, behavioral model parameter estimation based Test methods require the use of accurate models but no “training” is necessary, reducing Test deployment costs. In this work, a new Test generation approach is proposed that allows behavioral model parameter estimation to be performed from a single optimized OFDM data frame. A genetic multi-tone Test Stimulus optimization algorithm is developed to maximize the accuracy with which a nonlinear solver can determine RF transceiver model parameters from raw downconverted Test response data. The transceiver model proposed is the most comprehensive to date and includes AM-PM distortion and 5th order nonlinearity effects. Simulation results show that using the optimized multitone Test Stimulus, all the model parameters can be computed accurately using a single data acquisition (4X-5X faster than prior parameter estimation techniques and comparable to alternative Test times). Data from an experiment performed on a hardware prototype validates the proposed concept.
Kathryn J Jeffery - One of the best experts on this subject based on the ideXlab platform.
-
paradoxical enhancement of long term potentiation in poor learning rats at low Test Stimulus intensities
Experimental Brain Research, 1995Co-Authors: Kathryn J JefferyAbstract:Much empirical evidence and numerous theoretical models point to modification of synaptic efficacy as a mechanism for memory formation. To evaluate theoretical models, it is necessary to obtain quantitative experimental data relating learning to experimentally induced synaptic efficacy changes (such as long-term potentiation, LTP). An important problem in this type of experiment is how to quantify the LTP induced by a given stimulation protocol. Of relevance is the informally well-known observation that LTP magnitude appears to vary as a function of the intensity of the Stimulus used to evoke baseline responses. The present study found that using a measure of LTP that circumvents this variation, a strong negative correlation of learning with potentiation emerges. Spatial learning ability was compared with the magnitude of subsequent LTP induction as follows: rats underwent a day of spatial training in a watermaze followed by 5 days of bilateral perforant path tetanisation. Baseline electrophysiological responses were evoked over a range of Stimulus intensities (input/output [IO] curves) before and after tetanisation. Although LTP was observed across the whole of the IO curve, it showed a smooth decline with increasing current. The animals were then grouped according to their watermaze performance and IO curves compared between good and poor learners. After tetanisation, there was a negative withinanimal correlation between learning and evoked potential size with weak Test stimuli and a positive correlation with strong stimuli. The decline of LTP across the IO curve differed between good and poor spatial learners; the poor learners showed higher percentage potentiation with Test stimuli close to zero intensity, but a faster decrease in LTP across the curves. The findings are therefore: (1) the measured amount of LTP declined systematically with increasing Stimulus strength, and (2) the parameters of the decline correlated with spatial learning ability. These results raise two important issues. First, because measured LTP varied systematically across the IO curve, it appears that for quantitative analyses the widely used method of LTP measurement using a single Test Stimulus intensity risks missing significant features of the data. It is suggested that a measure be used that incorporates data from a range of Stimulus intensities. Second, when such a measure is used there is a striking negative correlation of spatial learning ability with LTP. These apparently paradoxical results are discussed.
Soumendu Bhattacharya - One of the best experts on this subject based on the ideXlab platform.
-
Optimized Multitone Test Stimulus Driven Diagnosis of RF Transceivers Using Model Parameter Estimation
2011 24th Internatioal Conference on VLSI Design, 2011Co-Authors: Aritra Banerjee, Abhijit Chatterjee, Vishwanath Natarajan, Ganesh Srinivasan, Soumendu BhattacharyaAbstract:Test time and Test complexity reduction has become a critical challenge in modern RF Testing. Prior “alternative” Test methods have achieved fast Testing at the cost of using supervised learning algorithms that require “training”. In contrast, behavioral model parameter estimation based Test methods require the use of accurate models but no “training” is necessary, reducing Test deployment costs. In this work, a new Test generation approach is proposed that allows behavioral model parameter estimation to be performed from a single optimized OFDM data frame. A genetic multi-tone Test Stimulus optimization algorithm is developed to maximize the accuracy with which a nonlinear solver can determine RF transceiver model parameters from raw downconverted Test response data. The transceiver model proposed is the most comprehensive to date and includes AM-PM distortion and 5th order nonlinearity effects. Simulation results show that using the optimized multitone Test Stimulus, all the model parameters can be computed accurately using a single data acquisition (4X-5X faster than prior parameter estimation techniques and comparable to alternative Test times). Data from an experiment performed on a hardware prototype validates the proposed concept.
David Yarnitsky - One of the best experts on this subject based on the ideXlab platform.
-
cpm Test reTest reliability standard vs single Test Stimulus protocols
Pain Medicine, 2016Co-Authors: Yelena Granovsky, Adi Millerbarmak, Oren Goldstein, Elliot Sprecher, David YarnitskyAbstract:Objectives. Assessment of pain inhibitory mechanisms using conditioned pain modulation (CPM) is relevant clinically in prediction of pain and analgesic efficacy. Our objective is to provide necessary estimates of intersession CPM reliability, to enable transformation of the CPM paradigm into a clinical tool. Design. Two cohorts of young healthy subjects (N = 65) participated in two dual-session studies. In Study I, a Bath-Thermode CPM protocol was used, with hot water immersion and contact heat as conditioning- and Test-stimuli, respectively, in a classical parallel CPM design introducing Test-Stimulus first, and then the conditioning- and repeated Test-stimuli in parallel. Study II consisted of two CPM protocols: 1) Two-Thermodes, one for each of the stimuli, in the same parallel design as above, and 2) single Test-Stimulus (STS) protocol with a single administration of a contact heat Test-Stimulus, partially overlapped in time by a remote shorter contact heat as conditioning Stimulus. Test–reTest reliability was assessed within 3–7 days. Results. The STS-CPM had superior reliability intraclass correlation (ICC2 , 1 = 0.59) over Bath-Thermode (ICC2 , 1 = 0.34) or Two-Thermodes (ICC2 , 1 = 0.21) protocols. The hand immersion conditioning pain had higher reliability than thermode pain (ICC2 , 1 = 0.76 vs ICC2 , 1 = 0.16). Conditioned Test-Stimulus pain scores were of good (ICC2 , 1 = 0.62) or fair (ICC2 , 1 = 0.43) reliability for the Bath-Thermode and the STS, respectively, but not for the Two-Thermodes protocol (ICC2 , 1 = 0.20). Conclusions. The newly developed STS-CPM paradigm was more reliable than other CPM protocols Tested here, and should be further investigated for its clinical relevance. It appears that large contact size of the conditioning-Stimulus and use of single rather than dual Test-Stimulus pain contribute to augmentation of CPM reliability.
