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The drilling of hard-to-cut high manganese steel materials is a difficulty in the field of machining. Research method for drilling temperature which has been commonly used is experimental method. The method has long-time and the high-cost drawbacks. Adopting error back neural network technology and using Matlab and C language programming method, in this paper neural network prediction model of drilling...
The drilling of hard-to-cut high manganese steel materials is a difficulty in the field of machining. Research method which has been commonly used is experimental method. This method has time-wasting and high-cost disadvantages. In this paper, adopting error back neural network technology and using Matlab and C language programming method, neural network prediction model of drilling force and torque...
As a difficult processing material, the drilling of the high manganese steel has been a difficulty among the mechanical processing industry, because its plastic deformation is great and produces the serious hardening phenomenon in the course of processing. During the process of drilling the high manganese steel, great cutting force will be produced, so the great power of the lathe can be consumed...
In this paper, we proposed an algorithm finding roots of algebraic polynomial based on PID (proportional-integral-derivative) neuron network, which the hidden layer of PID neural network was composed by proportion, integral and differential neurons. The PID neural network's input was error signal between the value of polynomial at and the given value 0, and its output was the root to find. The specific...
As for the distributed capacitor not taken into account in the conventional fault location algorithm, a single phase-ground fault location algorithm based on neural network with the distributed capacitor taken into account is proposed in this paper. The proposed algorithm uses neural network to correct the fault location distance dynamically. The MATLAB simulation results and dynamic modal experiments...
Prediction of electronic equipments and systemspsila Electromagnetic Compatibility (EMC) issues at early develop stages is inevitable for achieving their EMC discipline. This paper proposes a method to fast predict EMC problems based on Artificial Neural Networks (ANN). By means of choosing relevant Electromagnetic Interference parameters to compose of input prediction features, using the back propagation...
A new method for solving initial value problems in ordinary differential equations (ODES) is proposed in this paper. The algorithm of neural networks based on the cosine basis functions is studied in detail. The convergence theorem of neural networks algorithm is given and proved. The algorithm is validated by the simulation examples of ODES. The results show the proposed approach is more precise...
The relation between the amplitude-frequency response of FIR filter on type three with the linear phase and the parallel algorithm of neural network based on the activation matrix Hd-STC is researched in detail in the paper. The convergence theorem of the neural-network algorithm is presented and proved. The optimal design examples of high order FIR digital band-pass filters are given. The results...
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