A hybrid position/force controller is designed for the joint 2 and the joint 3 of the PUMA 560 robot. The hybrid controller includes a multilayered neural network, which can identify the dynamics of the contacted envi...
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ISBN:
(纸本)0819420123
A hybrid position/force controller is designed for the joint 2 and the joint 3 of the PUMA 560 robot. The hybrid controller includes a multilayered neural network, which can identify the dynamics of the contacted environment and can optimize the parameters of the PID controller. The experimental results show that after having been trained, the robot has both stable response to the training patterns and strong adaptive ability to the situation between the patterns.
Through the single parameter control, the virtual person model shape change rule in V-Stitcher is found. According the rule of shape change, put shoulder slope, chest Position, chest peak distance, abdomen, body width...
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ISBN:
(纸本)9781467344630;9781467344647
Through the single parameter control, the virtual person model shape change rule in V-Stitcher is found. According the rule of shape change, put shoulder slope, chest Position, chest peak distance, abdomen, body width, hip width, upper body length, posture, para posture, Bottom Position, upper body posture parameters which from the 3 d fitting software as the output vector, the human body characteristic parameters as input vector, establishing the multiple input and single output four layers bp neural network respectively in *** the basis of the training results, setting the transfer function for {tansig, logsig, purelin}, training function for {trainlm}, training step length for 1000, Ir for 0.01. Using MIV to chose the most effective parameters, to establish the multiple input and single output network structure. Compeared with the model from 3d scanner, the result indicates that this method can simulate shape feature of the human body well.
The PV generation system is an uncontrollable source and has an affect on the grid by randomness of output power. So we need to strengthen the study of PV output power forecast. In this paper, according to the related...
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ISBN:
(纸本)9783037856345
The PV generation system is an uncontrollable source and has an affect on the grid by randomness of output power. So we need to strengthen the study of PV output power forecast. In this paper, according to the related information of recent day with the same weather type, an improved wavelet neural network forecasting model without solar radiation was proposed. Furthermore, with the measured data came from a PV power plant, comparison experiments were made as opposed to improved wavelet neural network forecasting model and the wavelet neural network forecasting model with traditional learning algorithm. The experimental results indicate that the improved wavelet neural network forecasting model can significantly improve the precision of PV output power prediction. The comparison experiments considering solar radiation were also given, which also show the high precision and high efficiency of proposed model and algorithm.
Considering the limitation such as premature convergence and low, local convergence speed of genetic algorithm, some improvements were made for classical genetic algorithm. Firstly, a help operator was used to help in...
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ISBN:
(纸本)9781424410651
Considering the limitation such as premature convergence and low, local convergence speed of genetic algorithm, some improvements were made for classical genetic algorithm. Firstly, a help operator was used to help individuals of population according to the given probability. Secondly, the genetic individuals were separated into male individuals and female individuals, and consanguinity was fused into individuals. Two individuals with different sex could reproduce the next generation only if they were distant consanguinity individuals. Based on this improved genetic algorithm, an evolved neural network algorithm named IGI-bp algorithm was proposed. In this algorithm, genetic algorithm was used to optimize and design the structure, the initial weights and thresholds, the training ratio and momentum factor of neural network roundly. The disadvantage of neural networks that their structure and parameters were decided stochastically or by one's experience was overcome in this way, and the surge of algorithm was restrained. IGA-bp algorithm was used to recognize handwritten numerals, a recognition model of handwritten numerals based on bp neural network was found, and the handwritten numeral recognition scheme based on IGA-bp algorithm was proposed. The experimental results show that this algorithm is better than SGA-bp algorithm and traditional bp algorithm in both speed and precision of convergence, 14,e can obtain a better recognition effect using this algorithm.
In this paper, we propose a multi-scale Bayesian networks model and its inference algorithm. We use the multi-scale Bayesian networks model to segment the Synthetic Aperture Radar (SAR) image. The multi-scale Bayesian...
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ISBN:
(纸本)9781479927630
In this paper, we propose a multi-scale Bayesian networks model and its inference algorithm. We use the multi-scale Bayesian networks model to segment the Synthetic Aperture Radar (SAR) image. The multi-scale Bayesian networks is constructed accordance with the multi-scale sequence of SAR images, whose MAP value is performed using the Belief Propagation (bp) algorithm and the corresponding parameter estimation is finished by the Expectation-Maximization (EM) algorithm. Experimental results demonstrate that the proposed multi-scale Bayesian networks model outperform the single-scale Bayesian network model and Markov Random Field-Intersecting Cortical Model (MRF-CM).
With the development of mobile Internet applications, the fourth generation mobile communication (4G) has been widely used, low-density parity-check (LDPC) codes have gradually become the first choice for 4G communica...
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ISBN:
(纸本)9781467397957
With the development of mobile Internet applications, the fourth generation mobile communication (4G) has been widely used, low-density parity-check (LDPC) codes have gradually become the first choice for 4G communication because of its superior performance. For the short of traditional encoding and belief propagation (bp) decoding algorithm, this paper adopts a method of parallel processing for LDPC encoding and decoding which is finally realized on the mobile terminal. On the CUDA platform, CPU scheduling and GPU parallelization are used to process a large number of repeated operations so that parallel encoding algorithm and heterogeneous parallel bp algorithm are achieved and the efficiency is significantly improved.
The activation function for the node of Backpropagation (bp) network is the Sigmoid function. The gain of the Sigmoid is usually set equal to 1. Author considers that the fixative gain of the Sigmoid is disadvantageou...
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ISBN:
(纸本)7800033910
The activation function for the node of Backpropagation (bp) network is the Sigmoid function. The gain of the Sigmoid is usually set equal to 1. Author considers that the fixative gain of the Sigmoid is disadvantageous to the bp network to simulate the function of brain cells, and in some range it limits the convergent rate of bp network while training. Therefore, the paper presents a new improved bp network which the gain of the Sigmoid is variable while training. The improved bp network not only simulates brain cells better, but also converges faster while training.
This paper presents a new concept of Space-Airborne Bi-Static Linear Array SAR (SA-BiLASAR) imaging using array antenna, which inherited the advantages of conventional linear array antenna 3-D SAR and Bi-Static SAR. F...
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ISBN:
(纸本)9781467372978
This paper presents a new concept of Space-Airborne Bi-Static Linear Array SAR (SA-BiLASAR) imaging using array antenna, which inherited the advantages of conventional linear array antenna 3-D SAR and Bi-Static SAR. Firstly, the geometrical model and the signal model are established. Secondly, a time domain back projection imaging algorithm is presented for SA-BiLASAR data processing. In the end, the feasibility of the SA-BiLASAR and the imaging algorithm arc demonstrated by simulated results.
This paper describes a new method of the optimal design of electrical capacitance sensor, which is based on genetic algorithm, and a modified bp algorithm of image reconstruction for electrical capacitance tomography ...
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ISBN:
(纸本)0819447145
This paper describes a new method of the optimal design of electrical capacitance sensor, which is based on genetic algorithm, and a modified bp algorithm of image reconstruction for electrical capacitance tomography system. In the optimal design of sensor, the evenness of sensitivity distribution, the ratio of maximum capacitance to minimum capacitance and the ratio of full-pipe capacitance to empty-pipe capacitance are considered. In image reconstruction we use the curve of components ratio and threshold valve of pixel gray to improve the performance of bp algorithm. Better quality and accuracy is obtained in experiment.
The nonlinear compensation in the intelligent thermometer measurement instrumentation is introduced, and disadvantages of the compensation in hardware or software are discussed at present. The bp neural network method...
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ISBN:
(纸本)0780378652
The nonlinear compensation in the intelligent thermometer measurement instrumentation is introduced, and disadvantages of the compensation in hardware or software are discussed at present. The bp neural network method for the nonlinear compensation and its merits are proposed. The number of the hidden layer nodes and the improved algorithm are analyzed deeply, and the modeling process is presented in this paper. The example demonstrates that a more precise mathematical model of the thermocouple can be got based on the improved bp algorithm, which can be implemented by software, it is beneficial to improve the instrument accuracy.
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