In view of the occurrence of the coal and gas, outburst coal body separates in series of layer form, and tosses in a series of coal shell, and the morphological characteristics of the holes that formed in the coal lay...In view of the occurrence of the coal and gas, outburst coal body separates in series of layer form, and tosses in a series of coal shell, and the morphological characteristics of the holes that formed in the coal layers are very similar to some iterative morphological characteristics of the system state under highly nonlinear condition in chaos theory. Two kinds of morphology as well as their starting and end states are comparatively studied in this paper. The research results indicate that the outburst coal and rock system is in a chaotic state of lower nested hierarchy before outburst, and the process that lots of holes form owing to continuous outburst of a series of coal shells in a short time is in a rhythmical fast iterative stage of intermittent chaos state. And the state of the coal-gas system is in a stable equilibrium state after outburst. The behaviors of outburst occurrence, development and termination, based on the universal properties of various nonlinear mappings in describing complex problems, can be described by iterative operation in mathematics which uses the Logistic function f (x,μ)=μx(1-x) and the composite function F(3, x) = f(3)(x, μ) as kernel function. The primary equation of relative hole depth x and outburst parameter l in kernel function are given in this paper. The given results can deepen and enrich the understanding of physical essence of outburst.展开更多
In order to raise the detection precision of the extended binary phase shift keying （EBPSK） receiver, a detector based on the improved particle swarm optimization algorithm （IMPSO） and the BP neural network is des...In order to raise the detection precision of the extended binary phase shift keying （EBPSK） receiver, a detector based on the improved particle swarm optimization algorithm （IMPSO） and the BP neural network is designed. First, the characteristics of EBPSK modulated signals and the special filtering mechanism of the impacting filter are demonstrated. Secondly, an improved particle swarm optimization algorithm based on the logistic chaos disturbance operator and the Cauchy mutation operator is proposed, and the EBPSK detector is designed by utilizing the IMPSO-BP neural network. Finally, the simulation of the EBPSK detector based on the MPSO-BP neural network is conducted and the result is compared with that of the adaptive threshold-based decision, the BP neural network, and the PSO-BP detector, respectively. Simulation results show that the detection performance of the EBPSK detector based on the IMPSO-BP neural network is better than those of the other three detectors.展开更多
文摘In view of the occurrence of the coal and gas, outburst coal body separates in series of layer form, and tosses in a series of coal shell, and the morphological characteristics of the holes that formed in the coal layers are very similar to some iterative morphological characteristics of the system state under highly nonlinear condition in chaos theory. Two kinds of morphology as well as their starting and end states are comparatively studied in this paper. The research results indicate that the outburst coal and rock system is in a chaotic state of lower nested hierarchy before outburst, and the process that lots of holes form owing to continuous outburst of a series of coal shells in a short time is in a rhythmical fast iterative stage of intermittent chaos state. And the state of the coal-gas system is in a stable equilibrium state after outburst. The behaviors of outburst occurrence, development and termination, based on the universal properties of various nonlinear mappings in describing complex problems, can be described by iterative operation in mathematics which uses the Logistic function f (x,μ)=μx(1-x) and the composite function F(3, x) = f(3)(x, μ) as kernel function. The primary equation of relative hole depth x and outburst parameter l in kernel function are given in this paper. The given results can deepen and enrich the understanding of physical essence of outburst.
基金The National Natural Science Foundation of China (No.60872075)the National High Technology Research and Development Program of China (863 Program) (No. 2008AA01Z227)
文摘In order to raise the detection precision of the extended binary phase shift keying （EBPSK） receiver, a detector based on the improved particle swarm optimization algorithm （IMPSO） and the BP neural network is designed. First, the characteristics of EBPSK modulated signals and the special filtering mechanism of the impacting filter are demonstrated. Secondly, an improved particle swarm optimization algorithm based on the logistic chaos disturbance operator and the Cauchy mutation operator is proposed, and the EBPSK detector is designed by utilizing the IMPSO-BP neural network. Finally, the simulation of the EBPSK detector based on the MPSO-BP neural network is conducted and the result is compared with that of the adaptive threshold-based decision, the BP neural network, and the PSO-BP detector, respectively. Simulation results show that the detection performance of the EBPSK detector based on the IMPSO-BP neural network is better than those of the other three detectors.
