Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit feature...Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit features is realized by training results from neural network; the superior nonlinear mapping capability is competent for extracting fault features which are normalized and compressed subsequently. The complex classification problem on fault pattern recognition in analog circuit is transferred into feature processing stage by feature extraction based on neural network effectively, which improves the diagnosis efficiency. A fault diagnosis illustration validated this method.展开更多
The theories of diagnosing nonlinear analog circuits by means of the transient response testing are studled. Wavelet analysis is made to extract the transient response signature of nonlinear circuits and compress the ...The theories of diagnosing nonlinear analog circuits by means of the transient response testing are studled. Wavelet analysis is made to extract the transient response signature of nonlinear circuits and compress the signature dada. The best wavelet function is selected based on the between-category total scatter of signature. The fault dictionary of nonlinear circuits is constructed based on improved back-propagation（BP） neural network. Experimental results demonstrate that the method proposed has high diagnostic sensitivity and fast fault identification and deducibility.展开更多
In view of its use as reactivity theory,Conceptual Density Functional Theory(DFT),introduced by Parr et al.,has mainly concentrated up to now on the E = E[N,v] functional.However,different ensemble representations can...In view of its use as reactivity theory,Conceptual Density Functional Theory(DFT),introduced by Parr et al.,has mainly concentrated up to now on the E = E[N,v] functional.However,different ensemble representations can be used involving other variables also,such as ρ and μ.In this study,these different ensemble representations(E,?,F,and R) are briefly reviewed.Particular attention is then given to the corresponding second-order(functional) derivatives,and their analogieswith the second-order derivatives of thermodynamic state functions U,F,H,and G,which are related to each other via Legendre transformations,just as the DFT functionals(Nalewajski and Parr,1982).Starting from an analysis of the convexity/concavity of the DFT functionals,for which explicit proofs are discussed for some cases,the positive/negative definiteness of the associated kernels is derived and a detailed comparison is made with the thermodynamic derivatives.The stability conditions in thermodynamics are similar in structure to the convexity/concavity conditions for the DFT functionals.Thus,the DFT functionals are scrutinized based on the convexity/concavity of their two variables,to yield the possibility of establishing a relationship between the three second-order reactivity descriptors derived from the considered functional.Considering two ensemble representations,F and ?,F is eliminated as it has two dependent(extensive)variables,N and ρ.For ?,on the other hand,which is concave for both of its intensive variables(μ and υ),an inequality is derived from its three second-order(functional) derivatives:the global softness,the local softness,and the softness kernel.Combined with the negative value of the diagonal element of the linear response function,this inequality is shown to be compatible with the Berkowitz-Parr relationship,which relates the functional derivatives of ρ with υ,at constant N and μ.This was recently at stake upon quantifying Kohn's Nearsightedness of Electronic Matter.The analogy of the resulting inequality and the thermodynamic inequality for the G derivatives is highlighted.Potential research paths for this study are briefly addressed;the analogies between finite-temperature DFT response functions and their thermodynamic counterparts and the quest for analogous relationships,as derived in this paper,for DFT functionals that are analogues of entropy-dimensioned thermodynamic functions such as the Massieu function.展开更多
The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the ...The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the diagnostic results being sensitive to the specific values and random noise. This paper presents a data-driven fault diagnosis method for analog circuits based on the robust competitive agglomeration （RCA）, which can alleviate the incompleteness of the data by clustering with the competing process. And the robustness of the diagnostic results is enhanced by using the approach of robust statistics in RCA. A series of experiments are provided to demonstrate that RCA can classify the incomplete data with a high accuracy. The experimental results show that RCA is robust for the data needed to be classified as well as the parameters needed to be adjusted. The effectiveness of RCA in practical use is demonstrated by two analog circuits.展开更多
The analog-to-information convertor (AIC) is a successful practice of compressive sensing (CS) theory in the analog signal acquisition. This paper presents a multi-narrowband signals sampling and reconstruction model ...The analog-to-information convertor (AIC) is a successful practice of compressive sensing (CS) theory in the analog signal acquisition. This paper presents a multi-narrowband signals sampling and reconstruction model based on AIC and block sparsity. To overcome the practical problems, the block sparsity is divided into uniform block and non-uniform block situations, and the block restricted isometry property and sub-sampling limit in different situations are analyzed respectively in detail. Theoretical analysis proves that using the block sparsity in AIC can reduce the restricted isometric constant, increase the reconstruction probability and reduce the sub -sampling rate. Simulation results show that the proposed model can complete sub -sampling and reconstruction for multi-narrowband signals. This paper extends the application range of AIC from the finite information rate signal to the multi-narrowband signals by using the potential relevance of support sets. The proposed receiving model has low complexity and is easy to implement, which can promote the application of CS theory in the radar receiver to reduce the burden of analog-to digital convertor (ADC) and solve bandwidth limitations of ADC.展开更多
A method for robust analog fault diagnosis using hybrid neural networks is proposed. The primary focus of the paper is to provide robust diagnosis using a mechanism to deal with the problem of element tolerances and r...A method for robust analog fault diagnosis using hybrid neural networks is proposed. The primary focus of the paper is to provide robust diagnosis using a mechanism to deal with the problem of element tolerances and reduce testing time. The proposed approach is based on the fault dictionary diagnosis method and backward propagation neural network (BPNN) and the adaptive resonance theory (ART) neural network. Simulation results show that the method is robust and fast for fault diagnosis of analog circuits with tolerances.展开更多
Araneiforms are spider-like ground patterns that are widespread in the southern polar regions of Mars.A gas erosion process driven by the seasonal sublimation of CO_(2)ice was proposed as an explanation for their form...Araneiforms are spider-like ground patterns that are widespread in the southern polar regions of Mars.A gas erosion process driven by the seasonal sublimation of CO_(2)ice was proposed as an explanation for their formation,which cannot occur on Earth due to the high climatic temperature.In this study,we propose an alternative mechanism that attrib-utes the araneiform formation to the erosion of upwelling salt water from the subsurface,relying on the identification of the first terrestrial analog found in a playa of the Qaidam Basin on the northern Tibetan Plateau.Morphological analysis indicates that the structures in the Qaidam Basin have fractal features comparable to araneiforms on Mars.A numerical model is developed to investigate the araneiform formation driven by the water-diffusion mechanism.The simulation res-ults indicate that the water-diffusion process,under varying ground conditions,may be responsible for the diverse aranei-form morphologies observed on both Earth and Mars.Our numerical simulations also demonstrate that the orientations of the saltwater diffusion networks are controlled by pre-existing polygonal cracks,which is consistent with observations of araneiforms on Mars and Earth.Our study thus suggests that a saltwater-related origin of the araneiform is possible and has significant implications for water searches on Mars.展开更多
The effect of signal modulating noise in bistable stochastic resonance systems was studied theoretically and experimentally. A mathematical analysis was made on the bistable stochastic resonance model with small syste...The effect of signal modulating noise in bistable stochastic resonance systems was studied theoretically and experimentally. A mathematical analysis was made on the bistable stochastic resonance model with small system parameters. An analogue circuit was designed to perform the effect. The effect of signal modulating noise was shown in the analog simulation experiment. The analog experiment was conducted for two sinusoidal signals with different frequencies. The results show that there are a sinusoidal component corresponding to the input sinusoidal signal and a noise component presented as a Wiener process corresponding to the input white noise in the system output. By properly selecting system parameters, the effect of signal modulating noise can be manifested in the system output.展开更多
Approximation techniques are useful for implementing pattern recognizers, communication decoders and sensory processing algorithms where computational precision is not critical to achieve the desired system level perf...Approximation techniques are useful for implementing pattern recognizers, communication decoders and sensory processing algorithms where computational precision is not critical to achieve the desired system level performance. In our previous work, we had proposed margin propagation (MP) as an efficient piece-wise linear (PWL) approximation technique to a log-sum-exp function and had demonstrated its advantages for implementing probabilistic decoders. In this paper, we present a systematic and a generalized approach for synthesizing analog piecewise-linear (PWL) computing circuits using the MP principle. MP circuits use only addition, subtraction and threshold operations and hence can be implemented using universal conservation principles like the Kirchoff's current law. Thus, unlike the conventional translinear CMOS current-mode circuits, the operation of the MP circuits are functionally similar in weak, moderate and strong inversion regimes of the MOS transistor making the design approach bias-scalable. This paper presents measured results from MP circuits prototyped in a 0.5μm standard CMOS process verifying the bias-scalable property. As an example, we apply the synthesis approach towards designing linear classifiers and verify its performance using measured results.展开更多
基金the National Natural Science Fundation of China (60372001 90407007)the Ph. D. Programs Foundation of Ministry of Education of China (20030614006).
文摘Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit features is realized by training results from neural network; the superior nonlinear mapping capability is competent for extracting fault features which are normalized and compressed subsequently. The complex classification problem on fault pattern recognition in analog circuit is transferred into feature processing stage by feature extraction based on neural network effectively, which improves the diagnosis efficiency. A fault diagnosis illustration validated this method.
基金This project was supported by the National Nature Science Foundation of China(60372001)
文摘The theories of diagnosing nonlinear analog circuits by means of the transient response testing are studled. Wavelet analysis is made to extract the transient response signature of nonlinear circuits and compress the signature dada. The best wavelet function is selected based on the between-category total scatter of signature. The fault dictionary of nonlinear circuits is constructed based on improved back-propagation（BP） neural network. Experimental results demonstrate that the method proposed has high diagnostic sensitivity and fast fault identification and deducibility.
基金S.F. wishes to thank the Research Foundation Flanders (FWO) and the European Union＇s Horizon 2020 Marie Sklodowska-Curie grant (No. 706415) for financially suppor(ing his post-doctoral research at the ALGC group. ED.P. and P.G. acknowledge (he Research Fo
文摘In view of its use as reactivity theory,Conceptual Density Functional Theory(DFT),introduced by Parr et al.,has mainly concentrated up to now on the E = E[N,v] functional.However,different ensemble representations can be used involving other variables also,such as ρ and μ.In this study,these different ensemble representations(E,?,F,and R) are briefly reviewed.Particular attention is then given to the corresponding second-order(functional) derivatives,and their analogieswith the second-order derivatives of thermodynamic state functions U,F,H,and G,which are related to each other via Legendre transformations,just as the DFT functionals(Nalewajski and Parr,1982).Starting from an analysis of the convexity/concavity of the DFT functionals,for which explicit proofs are discussed for some cases,the positive/negative definiteness of the associated kernels is derived and a detailed comparison is made with the thermodynamic derivatives.The stability conditions in thermodynamics are similar in structure to the convexity/concavity conditions for the DFT functionals.Thus,the DFT functionals are scrutinized based on the convexity/concavity of their two variables,to yield the possibility of establishing a relationship between the three second-order reactivity descriptors derived from the considered functional.Considering two ensemble representations,F and ?,F is eliminated as it has two dependent(extensive)variables,N and ρ.For ?,on the other hand,which is concave for both of its intensive variables(μ and υ),an inequality is derived from its three second-order(functional) derivatives:the global softness,the local softness,and the softness kernel.Combined with the negative value of the diagonal element of the linear response function,this inequality is shown to be compatible with the Berkowitz-Parr relationship,which relates the functional derivatives of ρ with υ,at constant N and μ.This was recently at stake upon quantifying Kohn's Nearsightedness of Electronic Matter.The analogy of the resulting inequality and the thermodynamic inequality for the G derivatives is highlighted.Potential research paths for this study are briefly addressed;the analogies between finite-temperature DFT response functions and their thermodynamic counterparts and the quest for analogous relationships,as derived in this paper,for DFT functionals that are analogues of entropy-dimensioned thermodynamic functions such as the Massieu function.
基金supported by the National Natural Science Foundation of China (61202078 61071139)the National High Technology Research and Development Program of China (863 Program)(SQ2011AA110101)
文摘The data-driven fault diagnosis methods can improve the reliability of analog circuits by using the data generated from it. The data have some characteristics, such as randomness and incompleteness, which lead to the diagnostic results being sensitive to the specific values and random noise. This paper presents a data-driven fault diagnosis method for analog circuits based on the robust competitive agglomeration （RCA）, which can alleviate the incompleteness of the data by clustering with the competing process. And the robustness of the diagnostic results is enhanced by using the approach of robust statistics in RCA. A series of experiments are provided to demonstrate that RCA can classify the incomplete data with a high accuracy. The experimental results show that RCA is robust for the data needed to be classified as well as the parameters needed to be adjusted. The effectiveness of RCA in practical use is demonstrated by two analog circuits.
基金supported by the National Natural Science Foundation of China(61172159)
文摘The analog-to-information convertor (AIC) is a successful practice of compressive sensing (CS) theory in the analog signal acquisition. This paper presents a multi-narrowband signals sampling and reconstruction model based on AIC and block sparsity. To overcome the practical problems, the block sparsity is divided into uniform block and non-uniform block situations, and the block restricted isometry property and sub-sampling limit in different situations are analyzed respectively in detail. Theoretical analysis proves that using the block sparsity in AIC can reduce the restricted isometric constant, increase the reconstruction probability and reduce the sub -sampling rate. Simulation results show that the proposed model can complete sub -sampling and reconstruction for multi-narrowband signals. This paper extends the application range of AIC from the finite information rate signal to the multi-narrowband signals by using the potential relevance of support sets. The proposed receiving model has low complexity and is easy to implement, which can promote the application of CS theory in the radar receiver to reduce the burden of analog-to digital convertor (ADC) and solve bandwidth limitations of ADC.
文摘A method for robust analog fault diagnosis using hybrid neural networks is proposed. The primary focus of the paper is to provide robust diagnosis using a mechanism to deal with the problem of element tolerances and reduce testing time. The proposed approach is based on the fault dictionary diagnosis method and backward propagation neural network (BPNN) and the adaptive resonance theory (ART) neural network. Simulation results show that the method is robust and fast for fault diagnosis of analog circuits with tolerances.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB41000000)the Fundamental Research Funds for the Central Universities(WK2080000144)。
文摘Araneiforms are spider-like ground patterns that are widespread in the southern polar regions of Mars.A gas erosion process driven by the seasonal sublimation of CO_(2)ice was proposed as an explanation for their formation,which cannot occur on Earth due to the high climatic temperature.In this study,we propose an alternative mechanism that attrib-utes the araneiform formation to the erosion of upwelling salt water from the subsurface,relying on the identification of the first terrestrial analog found in a playa of the Qaidam Basin on the northern Tibetan Plateau.Morphological analysis indicates that the structures in the Qaidam Basin have fractal features comparable to araneiforms on Mars.A numerical model is developed to investigate the araneiform formation driven by the water-diffusion mechanism.The simulation res-ults indicate that the water-diffusion process,under varying ground conditions,may be responsible for the diverse aranei-form morphologies observed on both Earth and Mars.Our numerical simulations also demonstrate that the orientations of the saltwater diffusion networks are controlled by pre-existing polygonal cracks,which is consistent with observations of araneiforms on Mars and Earth.Our study thus suggests that a saltwater-related origin of the araneiform is possible and has significant implications for water searches on Mars.
基金Project (10276032) supportedjointly by the National Natural Science Foundation of China and by the Science Foundationof China Academy of Engineering Physics NSAFproject(2005038228) supported by Postdoctoral Science Foundation of China projectsupported by the Postdoctoral Science Foundation of Central South University(2005)
文摘The effect of signal modulating noise in bistable stochastic resonance systems was studied theoretically and experimentally. A mathematical analysis was made on the bistable stochastic resonance model with small system parameters. An analogue circuit was designed to perform the effect. The effect of signal modulating noise was shown in the analog simulation experiment. The analog experiment was conducted for two sinusoidal signals with different frequencies. The results show that there are a sinusoidal component corresponding to the input sinusoidal signal and a noise component presented as a Wiener process corresponding to the input white noise in the system output. By properly selecting system parameters, the effect of signal modulating noise can be manifested in the system output.
基金Supported by a Research Grant from The National Science Foundation(CCF:0728996)
文摘Approximation techniques are useful for implementing pattern recognizers, communication decoders and sensory processing algorithms where computational precision is not critical to achieve the desired system level performance. In our previous work, we had proposed margin propagation (MP) as an efficient piece-wise linear (PWL) approximation technique to a log-sum-exp function and had demonstrated its advantages for implementing probabilistic decoders. In this paper, we present a systematic and a generalized approach for synthesizing analog piecewise-linear (PWL) computing circuits using the MP principle. MP circuits use only addition, subtraction and threshold operations and hence can be implemented using universal conservation principles like the Kirchoff's current law. Thus, unlike the conventional translinear CMOS current-mode circuits, the operation of the MP circuits are functionally similar in weak, moderate and strong inversion regimes of the MOS transistor making the design approach bias-scalable. This paper presents measured results from MP circuits prototyped in a 0.5μm standard CMOS process verifying the bias-scalable property. As an example, we apply the synthesis approach towards designing linear classifiers and verify its performance using measured results.
