The Adaptive Particle Swarm Optimization method(A-PSO) combined the kinematic equations is proposed in this paper. The A-PSO is capable of solving the optimal solution of joint variables. The inverse kinematics mathematic model of the serial dangerous articles disposal manipulator with multiple degrees of freedom (Multi-DOFs) is built. In the proposed searching process, the position matrix and the pose matrix of the fitness function are adjusted by joints form, the steps of the particle swarm change with the global extremum. The proposed method is able to reduce the complexity of the analysis of inverse kinematic equations, and the adaptive solution can be obtained. Compared to the traditional PSO algorithm, the proposed A-PSO can obtain the logical joint variables in a more computationally efficient manner. The accuracy and efficiency of the proposed method is demonstrated in the case study.
Weak signal detection is a multidisciplinary application of detection methods, which through the use of different methods to study and analyze the statistical properties of signal and noise and use a variety of signal processing methods to analyze and process the input signal. Weak signals can be detected from strong noise to meet the requirements of modern scientific research and application of technology required for sophisticated detection technology. This paper describes the characteristics of weak signal detection and introduces the weak signal detection methods of linear and non-linear theory respectively. The emphasis is on comparing the current methods used in weak signal detection technology summarizing the characteristics of each method. Finally, is the development trend of weak signal detection. 2. Weak Signal Detection Using Linear Theory 2.1 Related Testing Related tests are mainly to the correlation analysis of signal and noise. The application of self-correlation detection technology is very wide, because the signal is periodic and the noise has no periodicity. The randomness of the noise is very strong. The auto-correlation operation utilizes the difference between the signal and the noise to realize the noise removal. Signal and noise are independent of each other. The definition of auto-correlation function shows that the signal itself has
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