Title : 
New neural networks based on Taylor series and their research
         
        
            Author : 
Chen Xiaoyun ; Ma Qiang ; Alkharobi, Talal
         
        
            Author_Institution : 
Coll. of Inf. Sci. & Eng., Lanzhou Univ., Lanzhou, China
         
        
        
        
        
        
            Abstract : 
This paper is mining in the essence of neural networks, and constructing 4 types of neural networks: (1) to construct a neural network based on Taylor series; (2) to construct a Taylor component neural network which brings in a radial basis function neuron as a prefix; (3) to construct a Fourier component neural network.Because of the relationships between these functions, the Taylor component NN and the Fourier component NN can be called Gauss series NN equivalently; (4) to construct a Gauss series Clustering neural network and to prove its equivalence with RBF NN in a limit situation.The development of new types of neural networks is playing an important role either to promote deepening study of neural networks theory or to provide new methods for applications.
         
        
            Keywords : 
Fourier series; data mining; pattern clustering; radial basis function networks; Fourier component neural network; Gauss series clustering neural network; Taylor component neural network; Taylor series; mining; radial basis function neuron; Computer science; Educational institutions; Electronic mail; Gaussian processes; Information science; Input variables; Neural networks; Neurons; Taylor series; Transfer functions; Fourier component neural network; Gauss series Clustering neural network; Taylor component neural network; Taylor series neural network; prediction; stock price;
         
        
        
        
            Conference_Titel : 
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
         
        
            Conference_Location : 
Beijing
         
        
            Print_ISBN : 
978-1-4244-4519-6
         
        
            Electronic_ISBN : 
978-1-4244-4520-2
         
        
        
            DOI : 
10.1109/ICCSIT.2009.5234726