We propose a new automatic method for the interpretation of potential fi eld data, called the RDAS–Euler method, which is based on Euler＇s deconvolution and analytic signal methods. The proposed method can estimate ...We propose a new automatic method for the interpretation of potential fi eld data, called the RDAS–Euler method, which is based on Euler＇s deconvolution and analytic signal methods. The proposed method can estimate the horizontal and vertical extent of geophysical anomalies without prior information of the nature of the anomalies（structural index）. It also avoids inversion errors because of the erroneous choice of the structural index N in the conventional Euler deconvolution method. The method was tested using model gravity anomalies. In all cases, the misfi t between theoretical values and inversion results is less than 10%. Relative to the conventional Euler deconvolution method, the RDAS–Euler method produces inversion results that are more stable and accurate. Finally, we demonstrate the practicability of the method by applying it to Hulin Basin in Heilongjiang province, where the proposed method produced more accurate data regarding the distribution of faults.展开更多
Compared to conventional magnetic data,magnetic gradient tensor data contain more high-frequency signal components,which can better describe the features of geological bodies.The directional analytic signal of the mag...Compared to conventional magnetic data,magnetic gradient tensor data contain more high-frequency signal components,which can better describe the features of geological bodies.The directional analytic signal of the magnetic gradient tensor is not easily interfered from the tilting magnetization,but it can infer the range of the fi eld source more accurately.However,the analytic signal strength decays faster with depth,making it diffi cult to identify deep fi eld sources.Balanced-boundary recognition can eff ectively overcome this disadvantage.We present here a balanced-boundary identifi cation technique based on the normalization of three-directional analytic signals from aeromagnetic gradient tensor data.This method can eff ectively prevent the fast attenuation of analytic signals.We also derive an Euler inversion algorithm of three-directional analytic signal derivative.By combining magnetic-anomaly model testing with the traditional magnetic anomaly interpretation method,we show that the boundary-recognition technology based on a magnetic gradient tensor analytic signal has a greater advantage in identifying the boundaries of the geological body and can better refl ect shallow anomalies.The characteristics of the Euler equation based on the magnetic anomaly direction to resolve the signal derivative have better convergence,and the obtained solution is more concentrated,which can obtain the depth and horizontal range information of the geological body more accurately.Applying the above method to the measured magneticanomaly gradient data from Baoding area,more accurate fi eld source information is obtained,which shows the feasibility of applying this method to geological interpretations.展开更多
The electric activities of neurons could be changed when ion channel block occurs in the neurons.External forcing currents with diversity are imposed on the regular network of Hodgkin-Huxley(HH) neuron,and target wave...The electric activities of neurons could be changed when ion channel block occurs in the neurons.External forcing currents with diversity are imposed on the regular network of Hodgkin-Huxley(HH) neuron,and target waves are induced to occupy the network.The forcing current I1 is imposed on neurons in a local region with m 0 ×m 0 nodes in the network,neurons in other nodes are imposed with another forcing current I2.Target wave could be developed to occupy the network when the gradient forcing current(I1-I2) exceeds certain threshold,and the formation of target wave is independent of the selection of boundary condition.It is also found that the developed target wave can decrease the negative effect of ion channel block and suppress the spiral wave,and thus channel noise is also considered.The potential mechanism of formation of target wave could be that the gradient forcing current(I1-I2) generates quasi-periodical signal in local area,and the propagation of quasi-periodical signal induces target-like wave due to mutual coupling among neurons in the network.展开更多
We propose a thoroughly optimal signal design strategy to achieve the Pareto boundary （boundary of the achievable rate region） with improper Gaussian signaling （IGS） on the Z-interference channel （Z-IC） under th...We propose a thoroughly optimal signal design strategy to achieve the Pareto boundary （boundary of the achievable rate region） with improper Gaussian signaling （IGS） on the Z-interference channel （Z-IC） under the assumption that the interference is treated as additive Gaussian noise. Specifically, we show that the Pareto boundary has two different schemes determined by the two paths manifesting the characteristic of improperly transmitted signals. In each scheme, we derive several concise closed-form expressions to calculate each user＇s optimally transmitted power, covariance, and pseudo-covariance of improperly transmitted signals. The effectiveness of the proposed optimal signal design strategy is supported by simulations, and the results clearly show the superiority of IGS. The proposed optimal signal design strategy also provides a simple way to achieve the required rate region, with which we also derive a closed-form solution to quickly find the circularity coefficient that maximizes the sum rate. Finally, we provide an in-depth discussion of the structure of the Pareto boundary, characterized by the channel coefficient, the degree of impropriety measured by the covariance, and the pseudo-covaxiance of signals transmitted by two users.展开更多
As a typical family of mono-component signals,the nonlinear Fourier basis {eikθa(t)}k∈Z,defined by the nontangential boundary value of the M¨obius transformation,has attracted much attention in the field of non...As a typical family of mono-component signals,the nonlinear Fourier basis {eikθa(t)}k∈Z,defined by the nontangential boundary value of the M¨obius transformation,has attracted much attention in the field of nonlinear and nonstationary signal processing in recent years.In this paper,we establish the Jackson's and Bernstein's theorems for the approximation of functions in Xp(T),1 p ∞,by the nonlinear Fourier basis.Furthermore,the analogous theorems for the approximation of functions in Hardy spaces by the finite Blaschke products are established.展开更多
基金supported by the National High Technology Research and Development Program of China(No.2006AA06A208)
文摘We propose a new automatic method for the interpretation of potential fi eld data, called the RDAS–Euler method, which is based on Euler＇s deconvolution and analytic signal methods. The proposed method can estimate the horizontal and vertical extent of geophysical anomalies without prior information of the nature of the anomalies（structural index）. It also avoids inversion errors because of the erroneous choice of the structural index N in the conventional Euler deconvolution method. The method was tested using model gravity anomalies. In all cases, the misfi t between theoretical values and inversion results is less than 10%. Relative to the conventional Euler deconvolution method, the RDAS–Euler method produces inversion results that are more stable and accurate. Finally, we demonstrate the practicability of the method by applying it to Hulin Basin in Heilongjiang province, where the proposed method produced more accurate data regarding the distribution of faults.
基金supported by the National Key R&D Program of China (No. 2017YFC0602204)。
文摘Compared to conventional magnetic data,magnetic gradient tensor data contain more high-frequency signal components,which can better describe the features of geological bodies.The directional analytic signal of the magnetic gradient tensor is not easily interfered from the tilting magnetization,but it can infer the range of the fi eld source more accurately.However,the analytic signal strength decays faster with depth,making it diffi cult to identify deep fi eld sources.Balanced-boundary recognition can eff ectively overcome this disadvantage.We present here a balanced-boundary identifi cation technique based on the normalization of three-directional analytic signals from aeromagnetic gradient tensor data.This method can eff ectively prevent the fast attenuation of analytic signals.We also derive an Euler inversion algorithm of three-directional analytic signal derivative.By combining magnetic-anomaly model testing with the traditional magnetic anomaly interpretation method,we show that the boundary-recognition technology based on a magnetic gradient tensor analytic signal has a greater advantage in identifying the boundaries of the geological body and can better refl ect shallow anomalies.The characteristics of the Euler equation based on the magnetic anomaly direction to resolve the signal derivative have better convergence,and the obtained solution is more concentrated,which can obtain the depth and horizontal range information of the geological body more accurately.Applying the above method to the measured magneticanomaly gradient data from Baoding area,more accurate fi eld source information is obtained,which shows the feasibility of applying this method to geological interpretations.
基金supported by the National Nature Science Foundation of China (Grant Nos. 11265008 and 11272242)
文摘The electric activities of neurons could be changed when ion channel block occurs in the neurons.External forcing currents with diversity are imposed on the regular network of Hodgkin-Huxley(HH) neuron,and target waves are induced to occupy the network.The forcing current I1 is imposed on neurons in a local region with m 0 ×m 0 nodes in the network,neurons in other nodes are imposed with another forcing current I2.Target wave could be developed to occupy the network when the gradient forcing current(I1-I2) exceeds certain threshold,and the formation of target wave is independent of the selection of boundary condition.It is also found that the developed target wave can decrease the negative effect of ion channel block and suppress the spiral wave,and thus channel noise is also considered.The potential mechanism of formation of target wave could be that the gradient forcing current(I1-I2) generates quasi-periodical signal in local area,and the propagation of quasi-periodical signal induces target-like wave due to mutual coupling among neurons in the network.
基金Project supported by the National Natural Science Foundation of China （Nos. 61601477 and 61601482）
文摘We propose a thoroughly optimal signal design strategy to achieve the Pareto boundary （boundary of the achievable rate region） with improper Gaussian signaling （IGS） on the Z-interference channel （Z-IC） under the assumption that the interference is treated as additive Gaussian noise. Specifically, we show that the Pareto boundary has two different schemes determined by the two paths manifesting the characteristic of improperly transmitted signals. In each scheme, we derive several concise closed-form expressions to calculate each user＇s optimally transmitted power, covariance, and pseudo-covariance of improperly transmitted signals. The effectiveness of the proposed optimal signal design strategy is supported by simulations, and the results clearly show the superiority of IGS. The proposed optimal signal design strategy also provides a simple way to achieve the required rate region, with which we also derive a closed-form solution to quickly find the circularity coefficient that maximizes the sum rate. Finally, we provide an in-depth discussion of the structure of the Pareto boundary, characterized by the channel coefficient, the degree of impropriety measured by the covariance, and the pseudo-covaxiance of signals transmitted by two users.
基金supported by National Natural Science Foundation of China (Grant Nos.11071261,60873088,10911120394)
文摘As a typical family of mono-component signals,the nonlinear Fourier basis {eikθa(t)}k∈Z,defined by the nontangential boundary value of the M¨obius transformation,has attracted much attention in the field of nonlinear and nonstationary signal processing in recent years.In this paper,we establish the Jackson's and Bernstein's theorems for the approximation of functions in Xp(T),1 p ∞,by the nonlinear Fourier basis.Furthermore,the analogous theorems for the approximation of functions in Hardy spaces by the finite Blaschke products are established.
