Nonlinear approximation is widely used in signal processing. Real-life signals can be modeled as functions of bounded variation. Thus the variable knot of approximating function could be self- adaptively chosen by bal...Nonlinear approximation is widely used in signal processing. Real-life signals can be modeled as functions of bounded variation. Thus the variable knot of approximating function could be self- adaptively chosen by balancing the total variation of the target function. In this paper, we adopt continuous piecewise linear approximation instead of the existing piecewise constants approximation. The results of experiments show that this new method is superior to the old one.展开更多
NUSH is a block cipher as a candidate for NESSIE. NUSH is analyzed by linear crypt-analysis . The complexity δ = (ε , η) of the attack consists of data complexity ε and time complexity η. Three linear approximati...NUSH is a block cipher as a candidate for NESSIE. NUSH is analyzed by linear crypt-analysis . The complexity δ = (ε , η) of the attack consists of data complexity ε and time complexity η. Three linear approximations are used to analyze NUSH with 64-bit block. When |K| = 128 bits, the complexities of three attacks are (258, 2124), (260, 278) and (262, 255) respectively. When |K| = 192 bits, the complexities of three attacks are (258, 2157) (260, 2%) and (262, 258) respectively. When |K| = 256 bits, the complexities of three attacks are (258, 2125), (260, 278) and (262, 253) respectively. Three linear approximations are used to analyze NUSH with 128-bit block. When |K|= 128 bits, the complexities of three attacks are (2122, 295), (2124, 257) and (2126, 252) respectively. When |K| = 192 bits, the complexities of three attacks are (2122, 2142), (2124, 275) and (2126, 258) respectively. When |K|= 256 bits, the complexities of three attacks are (2122, 2168), (2124, 281) and (2126, 264) respectively. Two linear approximations are used to analyze NUSH with 256-bit block. When |K|= 128 bits, the complexities of two attacks are (2252, 2122) and (2254, 2119) respectively. When |K|= 192 bits, the complexities of two attacks are (2252, 2181) and (2254, 2177) respectively. When |K|=256 bits, the complexities of two attacks are (2252, 2240) and (2254, 2219) respectively. These results show that NUSH is not immune to linear cryptanalysis, and longer key cannot enhance the security of NUSH.展开更多
A hybrid system of the fuzzy c-means （FCM） clustering algorithm and adaptive-two-stage linear approximation was presented for nonlinear distortion cancellation of radio frequency （RF） power amplifier （PA）. This ...A hybrid system of the fuzzy c-means （FCM） clustering algorithm and adaptive-two-stage linear approximation was presented for nonlinear distortion cancellation of radio frequency （RF） power amplifier （PA）. This mechanism can effectively eliminate noise, adaptively model PA＇s instantaneous change, and efficiently correct nonlinear distortion. This article puts forward the FCM clustering algorithm for clustering received signals to eliminate white noise, and then uses the adaptive-two-stage linear approximation to fit the inverse function of the amplitude＇s and phase＇s nonlinear mapping during the training phase. Parameters of the linear function and similarity function are trained using the gradient-descent and minimum mean-square error criteria. The proposed approach＇s training results is directly employed to eliminate sampling signal＇s nonlinear distortion. This hybrid method is realized easier than the multi-segment linear approximation and could reduce the received signal＇s bit error rate （BER） more efficiently.展开更多
Damping is critical for the roll motion response of a ship in waves. A common method for the assessment of damping in a ship’s rolling motion is to perform a free-decay experiment in calm water. In this paper, we pro...Damping is critical for the roll motion response of a ship in waves. A common method for the assessment of damping in a ship’s rolling motion is to perform a free-decay experiment in calm water. In this paper, we propose an approach for estimating nonlinear damping that involves a linear exponential analytical approximation of the experimental roll free-decay amplitudes, fol- lowed by parametric identification based on the asymptotic method. The restoring moment can be strongly nonlinear. To validate this method, we first analyzed numerically simulated roll free-decay data using rolling equations with two alternative parametric forms: linear-plus-quadratic and linear-plus-cubic damping. By doing so, we obtained accurate estimates of nonlinear damping coefficients, even for large initial roll amplitudes. Then, we applied the proposed method to real free-decay data obtained from a scale model of a bulk barrier, and found the simulated results to be in good agreement with the experimental data. Using only free-decay peak data, the proposed method can be used to estimate nonlinear roll-damping coefficients for conditions with a strongly nonlinear restoring moment and large initial roll amplitudes.展开更多
This article is devoted to the problem of composite control design for continuous nonlinear singularly perturbed(SP)system using approximate feedback linearization(AFL)method.The essence of AFL method lies in the feed...This article is devoted to the problem of composite control design for continuous nonlinear singularly perturbed(SP)system using approximate feedback linearization(AFL)method.The essence of AFL method lies in the feedback linearization only of a certain part of the original nonlinear system.According to AFL approach,we suggest to solve feedback linearization problems for continuous nonlinear SP system by reducing it to two feedback linearization problems for slow and fast subsystems separately.The resulting AFL control is constructed in the form of asymptotic composition(composite control).Standard procedure for the composite control design consists of the following steps:1)system decomposition,2)solution of control problem for fast subsystem,3)solution of control problem for slow subsystem,4)construction of the resulting control in the form of the composition of slow and fast controls.The main difficulty during system decomposition is associated with dynamics separation condition for nonlinear SP system.To overcome this,we propose to change the sequence of the design procedure:1)solving the control problem for fast state variables part,2)system decomposition,3)solving the control problem for slow state variables part,4)construction of the resulting composite control.By this way,fast feedback linearizing control is chosen so that the dynamics separation condition would be met and the fast subsystem would be stabilizable.The application of the proposed approach is illustrated through several examples.展开更多
In algorithms of nonlinear Kalman filter, the so-called extended Kalman filter algorithm actually uses first-order Taylor expansion approach to transform a nonlinear system into a linear system. It is obvious that thi...In algorithms of nonlinear Kalman filter, the so-called extended Kalman filter algorithm actually uses first-order Taylor expansion approach to transform a nonlinear system into a linear system. It is obvious that this algorithm will bring some systematic deviations because of ignoring nonlinearity of the system. This paper presents two extended Kalman filter algorithms for nonlinear systems, called second-order nonlinear Kalman particle filter algorithms, by means of second-order Taylor expansion and linearization approximation, and correspondingly two recursive formulas are derived. A simulation example is given to illustrate the effectiveness of two algorithms. It is shown that the extended Kalman particle filter algorithm based on second-order Taylor expansion has a more satisfactory performance in reducing systematic deviations and running time in comparison with the extended Kalman filter algorithm and the other second-order nonlinear Kalman particle filter algorithm.展开更多
文摘Nonlinear approximation is widely used in signal processing. Real-life signals can be modeled as functions of bounded variation. Thus the variable knot of approximating function could be self- adaptively chosen by balancing the total variation of the target function. In this paper, we adopt continuous piecewise linear approximation instead of the existing piecewise constants approximation. The results of experiments show that this new method is superior to the old one.
基金This work was supported by 973 Project (Grant No. G1999035802) and the National Natural Science Foundation of China (Grant No. 19931010) .
文摘NUSH is a block cipher as a candidate for NESSIE. NUSH is analyzed by linear crypt-analysis . The complexity δ = (ε , η) of the attack consists of data complexity ε and time complexity η. Three linear approximations are used to analyze NUSH with 64-bit block. When |K| = 128 bits, the complexities of three attacks are (258, 2124), (260, 278) and (262, 255) respectively. When |K| = 192 bits, the complexities of three attacks are (258, 2157) (260, 2%) and (262, 258) respectively. When |K| = 256 bits, the complexities of three attacks are (258, 2125), (260, 278) and (262, 253) respectively. Three linear approximations are used to analyze NUSH with 128-bit block. When |K|= 128 bits, the complexities of three attacks are (2122, 295), (2124, 257) and (2126, 252) respectively. When |K| = 192 bits, the complexities of three attacks are (2122, 2142), (2124, 275) and (2126, 258) respectively. When |K|= 256 bits, the complexities of three attacks are (2122, 2168), (2124, 281) and (2126, 264) respectively. Two linear approximations are used to analyze NUSH with 256-bit block. When |K|= 128 bits, the complexities of two attacks are (2252, 2122) and (2254, 2119) respectively. When |K|= 192 bits, the complexities of two attacks are (2252, 2181) and (2254, 2177) respectively. When |K|=256 bits, the complexities of two attacks are (2252, 2240) and (2254, 2219) respectively. These results show that NUSH is not immune to linear cryptanalysis, and longer key cannot enhance the security of NUSH.
基金supported by the National Natural Science Foundation of China(61171104)
文摘A hybrid system of the fuzzy c-means （FCM） clustering algorithm and adaptive-two-stage linear approximation was presented for nonlinear distortion cancellation of radio frequency （RF） power amplifier （PA）. This mechanism can effectively eliminate noise, adaptively model PA＇s instantaneous change, and efficiently correct nonlinear distortion. This article puts forward the FCM clustering algorithm for clustering received signals to eliminate white noise, and then uses the adaptive-two-stage linear approximation to fit the inverse function of the amplitude＇s and phase＇s nonlinear mapping during the training phase. Parameters of the linear function and similarity function are trained using the gradient-descent and minimum mean-square error criteria. The proposed approach＇s training results is directly employed to eliminate sampling signal＇s nonlinear distortion. This hybrid method is realized easier than the multi-segment linear approximation and could reduce the received signal＇s bit error rate （BER） more efficiently.
基金support from the National Natural Science Foundation of China (No. 5160 9224)the Major Program of National Natural Science Foundation of China (No. 51490675)the Fundamental Research Funds for the Central Universities (No. 201513056)
文摘Damping is critical for the roll motion response of a ship in waves. A common method for the assessment of damping in a ship’s rolling motion is to perform a free-decay experiment in calm water. In this paper, we propose an approach for estimating nonlinear damping that involves a linear exponential analytical approximation of the experimental roll free-decay amplitudes, fol- lowed by parametric identification based on the asymptotic method. The restoring moment can be strongly nonlinear. To validate this method, we first analyzed numerically simulated roll free-decay data using rolling equations with two alternative parametric forms: linear-plus-quadratic and linear-plus-cubic damping. By doing so, we obtained accurate estimates of nonlinear damping coefficients, even for large initial roll amplitudes. Then, we applied the proposed method to real free-decay data obtained from a scale model of a bulk barrier, and found the simulated results to be in good agreement with the experimental data. Using only free-decay peak data, the proposed method can be used to estimate nonlinear roll-damping coefficients for conditions with a strongly nonlinear restoring moment and large initial roll amplitudes.
基金supported by Russian Foundation for Basic Research(No.15-08-06859a)and by the Ministry of Education and Science of the Russian Federation in the framework of the basic part of the state order(No.2.8629.2017).
文摘This article is devoted to the problem of composite control design for continuous nonlinear singularly perturbed(SP)system using approximate feedback linearization(AFL)method.The essence of AFL method lies in the feedback linearization only of a certain part of the original nonlinear system.According to AFL approach,we suggest to solve feedback linearization problems for continuous nonlinear SP system by reducing it to two feedback linearization problems for slow and fast subsystems separately.The resulting AFL control is constructed in the form of asymptotic composition(composite control).Standard procedure for the composite control design consists of the following steps:1)system decomposition,2)solution of control problem for fast subsystem,3)solution of control problem for slow subsystem,4)construction of the resulting control in the form of the composition of slow and fast controls.The main difficulty during system decomposition is associated with dynamics separation condition for nonlinear SP system.To overcome this,we propose to change the sequence of the design procedure:1)solving the control problem for fast state variables part,2)system decomposition,3)solving the control problem for slow state variables part,4)construction of the resulting composite control.By this way,fast feedback linearizing control is chosen so that the dynamics separation condition would be met and the fast subsystem would be stabilizable.The application of the proposed approach is illustrated through several examples.
文摘In algorithms of nonlinear Kalman filter, the so-called extended Kalman filter algorithm actually uses first-order Taylor expansion approach to transform a nonlinear system into a linear system. It is obvious that this algorithm will bring some systematic deviations because of ignoring nonlinearity of the system. This paper presents two extended Kalman filter algorithms for nonlinear systems, called second-order nonlinear Kalman particle filter algorithms, by means of second-order Taylor expansion and linearization approximation, and correspondingly two recursive formulas are derived. A simulation example is given to illustrate the effectiveness of two algorithms. It is shown that the extended Kalman particle filter algorithm based on second-order Taylor expansion has a more satisfactory performance in reducing systematic deviations and running time in comparison with the extended Kalman filter algorithm and the other second-order nonlinear Kalman particle filter algorithm.
