PURPOSE:To perform the fast positive Fourier transform of a sampling waveform or the inverse transform thereof to the vibration waveform of a complex Fourier spectrum by superposing the values of a plurality of the output neurons of respective neural networks one upon another. CONSTITUTION:...
Toyoshima, “Real-Time Discrimination of Ventricular Tachyarrhythmia with Fourier-Transform Neural Network”, IEEE Transactions on Biomedical Engineering, Vol. 46, No. 2, 179-185, 1999. :Minami K, Nakajima H and Toyoshima T 1999 Real-time discrimination of ventricular tachyarrhythmia with Fourier- ...
Shin S G,Jin S I,Shin S Y et al.Optical neural network using fractional Fourier transform, log-likelihood, and parallelism.Optics Communication. 1998Shin, S. G., Jin, S., Shin, S. Y. et al. , Optical neural network using fractional Fourier transform, log-likelihood, and parallelism, ...
Levenberg Marquardt Back-Propagation algorithm is used to train the network. The results obtained have better efficiency then the previously proposed methods. Keywords: Cardiac Arrhythmias; Neural Network; Electrocardiogram (ECG); Fast Fourier Transform (FFT)...
Kumar, R., Gothwal, H., Kedawat, S.: Cardiac arrhythmias detection in an ECG beat signal using fast fourier transform and artificial neural network. J. Biomed. Sci. Eng. 4, 289–296 (2011) 14. LeCun, Y., Mathieu, M., Henaff, M.: Fast training of convolutional networks through ...
Minami K-I, Nakajima H and Toyoshima T (1999) Real-time discrimination of ventricular tachyarrhythmia with Fourier-transform neural network. IEEE Trans Biomed Eng 179–185 Gothwal H, Kedawat S, Kumar R (2011) Cardiac arrhythmias detection in an ECG beat signal using fast Fourier transform and...
The calculation method for weights of orthogonal Fourier series neural networks on the grounds of multidimensional discrete Fourier transform is presented. The method proposed represents high speed of operation and outlier robustness. It allows easy reduction of network structure following its training proce...
We combine the nonlinear Fourier transform (NFT) signal processing with machine learning methods for solving the direct spectral problem associated with the nonlinear Schrödinger equation. The latter is one of the core nonlinear science models emergin
快速傅里叶变换 (fast Fourier transform) 多项式 我们将多项式记为: F ( x ) = a 0 + a 1 x + a 2 x 2 + …… + a n x n F(x)=a_0+a_1x+a_2x^2+……+a_nx^n F(x)=a0+a1x+a2x2+……+anxn &nb... ...
The raw signal was pretreated using short time Fourier transform(STFT) to obtain the corresponding time-frequency map.Then, the feature of the time-frequency map was adaptively extracted by using a convolutional neural network(CNN). The effects of the pretreatment method, and the hyper parameters ...