Multiple state variables governed by internal processes within the human body remain unobserved. On a number of occasions, these states are linked to point process bioelectric and biochemical observations coupled toge...
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Multiple state variables governed by internal processes within the human body remain unobserved. On a number of occasions, these states are linked to point process bioelectric and biochemical observations coupled together with continuous-valued variables. These observations provide a means to estimate the latent states of interest. We develop a state-space method to estimate unobserved sympathetic arousal and energy production states from skin conductance and cortisol data respectively, comprising of a marked point process and a continuous-valued observation. The method involves Bayesian filtering applied within an expectation-maximization (EM) framework for state estimation and model parameter recovery. Results are evaluated on both simulated and experimental data. On experimental skin conductance data, high arousal levels are generally detected during cognitive stress periods and lower values are detected during relaxation. Results are also in conformity with general physiology for cortisol data. On separate experimental data, skin conductance-based estimates are validated/cross-checked with functional Near Infrared Spectroscopy features. Estimation is also performed on heart rate and skin conductance data to illustrate the method's wider applicability. We also compare the method with earlier approaches. We show how it outperforms a previous method for cortisol-based energy estimation, and its superiority to earlier methods for estimating sympathetic arousal. The EM approach is thus able to estimate latent physiological states within the body from point process bioelectric and biochemical phenomena. The method could be applied in wearable monitoring and automated closed-loop therapy delivery for patients diagnosed with certain types of neuropsychiatric or hormone disorders.
Sidelobes commonly disturb synthetic aperture radar (SAR) image understanding and interpretation. Traditional spatially variant filtering algorithms achieve a superior tradeoff between sidelobe suppression and resolut...
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Sidelobes commonly disturb synthetic aperture radar (SAR) image understanding and interpretation. Traditional spatially variant filtering algorithms achieve a superior tradeoff between sidelobe suppression and resolution preservation by means of adaptively calculating filtering parameters under some specific restrictions, such as filter design restriction and minimum amplitude constraint (MAC). These restriction aims to obtain an efficient analytical solution for filters, which is easy to calculate under unsupervised conditions. However, the restriction scope is so narrow that the suppression performance achieved by these filters is limited. Also, since the unsupervised optimization based on MAC indiscriminately minimizes amplitude, the main-lobe loss is unavoidable. To further improve the performance, a spatially variant convolution neural network (SVNN) is proposed, which consists of two core modules. One is the spatially variant filter generation (SVFG) module, adaptively generating superior spatially variant filters under more relaxed restrictions. The other is a paralleled shifted convolution (PSC) module, converting the signal format to achieve a fast and parallel spatially variant filtering process. Benefiting from more relaxed filter restrictions, the novel network successfully achieves better performance on sidelobe suppression. In addition, with supervised optimization based on another more accurate restriction, namely, minimum error constraint (MEC), the proposed algorithm also achieves superior main-lobe maintenance. All of them are validated by comparative experiments based on satellite data from GaoFen-3 and TerraSAR-X, and our proposed method achieves state-of-the-art performance. The entire project is available at https://***/suoyuxi/SVNN.
Device and circuit performance such as drain current and delay time varies stochastically due to uncontrollable factors in the fabrication processes. In this paper, a new method that represents the variation of the pe...
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Device and circuit performance such as drain current and delay time varies stochastically due to uncontrollable factors in the fabrication processes. In this paper, a new method that represents the variation of the performance as worst case parameters in a MOSFET model is proposed. The variation of the performance can be expressed as a linear combination of several process-related parameters of the MOSFET model. Because of this fact, the worst case of parameters which corresponds to the worst case of performance can be directly and uniformly determined. Therefore, the calculation time of worst case parameters can be reduced by this method. The worst case parameter sets calculated by this method enable designers to estimate circuit performance variations accurately and easily. The capability of this method is verified in the variation analysis of drain current.
Critical systems must be able to with stand attacks, failures, and accidents with acceptable levels of information integrity. A four-step method has been developed for analyzing survivability in distributed systems. T...
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Critical systems must be able to with stand attacks, failures, and accidents with acceptable levels of information integrity. A four-step method has been developed for analyzing survivability in distributed systems. The following case study describes the application of this method to a large-scale distributed health care system.
This correspondence presents a study of the quantization effects in the finite precision LMS algorithm with power-of-two step sizes, Deterministic nonlinear recursions are presented for the mean and second-moment matr...
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This correspondence presents a study of the quantization effects in the finite precision LMS algorithm with power-of-two step sizes, Deterministic nonlinear recursions are presented for the mean and second-moment matrix of the weight vector about the Wiener weight for white Gaussian data models and small algorithm step size mu. The numerical solutions of these recursions are shown to agree very closely with the Monte Carlo simulations during an phases of the adaptation process. Design examples demonstrate the selection of the number of quantizer bits and the adaptation step size mu to yield a desired transient behavior and cancellation performance. The results obtained indicate that previous models are too conservative in predicting the converged MSE for a given number of bits.
In this paper we resolve several important open issues pertaining to a worst-case control-oriented system identification problem known as identification In H-infinity. First, a method Is presented for developing confi...
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In this paper we resolve several important open issues pertaining to a worst-case control-oriented system identification problem known as identification In H-infinity. First, a method Is presented for developing confidence that certain a priori information available for identification is not invalid. This method requires the solution of a certain nondifferentiable convex program. Second, an essentially optimal identification algorithm is constructed. This algorithm is (worst-case strongly) optimal to within a factor of two. Finally, new upper and lower bounds on the optimal identification error are derived and used to estimate the identification error associated with the given algorithm. Interestingly, the development of each of these results draws heavily upon the classical Nevanlinna-Pick interpolation theory. As such, our results establish a clear link between the areas of system identification and optimal interpolation theory. Both the formulation and techniques in this paper are applicable to problems where the frequency data available for identification may essentially be arbitrarily distributed.
This paper describes an integrated activity in engineering ethics and responsibility extending over three class periods in an electrical engineering senior seminar. The activity begins by having the students discuss (...
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This paper describes an integrated activity in engineering ethics and responsibility extending over three class periods in an electrical engineering senior seminar. The activity begins by having the students discuss (using role play) and choose a course of action with respect to a consumer safety product. The choices involve a tradeoff between product cost (and resulting market attractiveness) and the level of safety provided. After they make their decision, we surprise them with a civil court trial, in which they are challenged by a "plaintiff's attorney" to justify their decisions in an adversarial atmosphere. A great deal of interest is generated because the role play becomes real, in the sense that they are called on to defend their actual decisions, rather than reviewing the words and actions of others. They also learn about tort law and liability. Students often describe the mock court class as "the best I ever had in engineering."
Information gathered from multiple sources on the Web often exhibits conflicts. This phenomenon motivates the need of truth discovery, which aims to automatically find the true claim among multiple conflicting claims....
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Information gathered from multiple sources on the Web often exhibits conflicts. This phenomenon motivates the need of truth discovery, which aims to automatically find the true claim among multiple conflicting claims. Existing truth discovery methods are mainly based on iterative updates, optimization or probabilistic models. Although these methods have shown their own effectiveness, they have a common limitation. These methods do not model relationships between each pair of source and target such that they do not well capture the underlying interactions in the data. In this paper, we propose a new model for truth discovery, learning the representations of sources and claims automatically from the interactions between sources and targets. Our model first constructs a heterogenous network including source-claim, source-source and truth-claim relationships. It then embeds the network into a low dimensional space such that trustworthy sources and true claims are close. In this way, truth discovery can be conveniently performed in the embedding space. Moreover, our model can be implemented in both semi-supervised and un-supervised manners to deal with the label scarcity problem in practical truth discovery. Experiments on three real-world datasets demonstrate that our model outperforms existing state-of-the-art methods for truth discovery.
The method of sections for constructing reachable sets of nonlinear control systems with constraints on the control and system state is considered. The proposed algorithms are based on the application of complexes of ...
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The method of sections for constructing reachable sets of nonlinear control systems with constraints on the control and system state is considered. The proposed algorithms are based on the application of complexes of programs whose functional content contains methods for calculating an optimal control for various constraints on control and system coordinates. The problems of many-processor computing technology are discussed and the results of numerical experiments are presented.
A case study analyzed the introduction of computer-aided design (CAD) in a Swedish engineering company. The focus was on the process of change and the repercussions of the new technology on work organization and comm...
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A case study analyzed the introduction of computer-aided design (CAD) in a Swedish engineering company. The focus was on the process of change and the repercussions of the new technology on work organization and communication patterns within the company. Data were collected by formal interviews, informal talks, surveys, and observations. The designers had received the new technology favorably and were impatient about the pace of change. However, the introduction of CAD had less than desirable effects on the work situation of the designers and on the cooperation with other functions that had been envisaged, since the development of the system was limited to a small group close to the design management. The study confirmed that CAD will have little effect on a bureaucratic organization unless the change is included as an explicit objective. A joint forum for outlining a strategy is needed for the full utilization of any new technology.
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