An improved hybrid Time of Arrival (ToA)/ Angle of Arrival (AoA) location algorithm by adopting Gauss-Newton iterative algorithm is proposed. It is with the advantage of fast convergence and combining with the grid-se...An improved hybrid Time of Arrival (ToA)/ Angle of Arrival (AoA) location algorithm by adopting Gauss-Newton iterative algorithm is proposed. It is with the advantage of fast convergence and combining with the grid-search-based method to optimize the initial object coordinates of the iteration, meanwhile, under the condition of small measurement errors caused by noises of ToA and AoA, the algorithm performance can be improved effectively. In the Non-Line-of-Sight (NLoS) environments of the Wireless Sensor Network (WSN), simulation results show that improved accuracy is gained with moderate flexibility and fast steady convergence compared with the existing algorithms.展开更多
A kind of second order algorithm--recursive approximate Newton algorithm was given by Karayiannis. The algorithm was simplified when it was formulated. Especially, the simplification to matrix Hessian was very reluct...A kind of second order algorithm--recursive approximate Newton algorithm was given by Karayiannis. The algorithm was simplified when it was formulated. Especially, the simplification to matrix Hessian was very reluctant, which led to the loss of valuable information and affected performance of the algorithm to certain extent. For multi layer feed forward neural networks, the second order back propagation recursive algorithm based generalized cost criteria was proposed. It is proved that it is equivalent to Newton recursive algorithm and has a second order convergent rate. The performance and application prospect are analyzed. Lots of simulation experiments indicate that the calculation of the new algorithm is almost equivalent to the recursive least square multiple algorithm. The algorithm and selection of networks parameters are significant and the performance is more excellent than BP algorithm and the second order learning algorithm that was given by Karayiannis.展开更多
基金supported by National Natural Science Foundation of China under Grant No.61172073State Key Laboratory of Networking and Switching Technology (Beijing Universityof Posts and Telecommunications) under Grant No.SKLNST-2009-1-09+1 种基金Open Research Fund of National Mobile Communications Research Laboratory, Southeast University, P. R.ChinaChina Fundamental Research Funds for the Central Universities:Beijing Jiaotong University
文摘An improved hybrid Time of Arrival (ToA)/ Angle of Arrival (AoA) location algorithm by adopting Gauss-Newton iterative algorithm is proposed. It is with the advantage of fast convergence and combining with the grid-search-based method to optimize the initial object coordinates of the iteration, meanwhile, under the condition of small measurement errors caused by noises of ToA and AoA, the algorithm performance can be improved effectively. In the Non-Line-of-Sight (NLoS) environments of the Wireless Sensor Network (WSN), simulation results show that improved accuracy is gained with moderate flexibility and fast steady convergence compared with the existing algorithms.
文摘A kind of second order algorithm--recursive approximate Newton algorithm was given by Karayiannis. The algorithm was simplified when it was formulated. Especially, the simplification to matrix Hessian was very reluctant, which led to the loss of valuable information and affected performance of the algorithm to certain extent. For multi layer feed forward neural networks, the second order back propagation recursive algorithm based generalized cost criteria was proposed. It is proved that it is equivalent to Newton recursive algorithm and has a second order convergent rate. The performance and application prospect are analyzed. Lots of simulation experiments indicate that the calculation of the new algorithm is almost equivalent to the recursive least square multiple algorithm. The algorithm and selection of networks parameters are significant and the performance is more excellent than BP algorithm and the second order learning algorithm that was given by Karayiannis.
