scholarly journals Determining the Weights of A Fourier Series Neural Network on the Basis of the Multidimensional Discrete Fourier Transform

2008 ◽  
Vol 18 (3) ◽  
pp. 369-375 ◽  
Author(s):  
Krzysztof Halawa
Keyword(s):  
Neural Network ◽  
Fourier Transform ◽  
Fourier Series ◽  
Computational Complexity ◽  
Discrete Fourier Transform ◽  
Dynamic Systems ◽  
Low Computational Complexity

Determining the Weights of A Fourier Series Neural Network on the Basis of the Multidimensional Discrete Fourier TransformThis paper presents a method for training a Fourier series neural network on the basis of the multidimensional discrete Fourier transform. The proposed method is characterized by low computational complexity. The article shows how the method can be used for modelling dynamic systems.

Non-Invasive Optical Blood Glucose Measurement based on Discrete Fourier Transform and Fast Artificial Neural Network: Fasting Normal Glucose Participants Case Study

2019 ◽  
Author(s):  
Renan Prasta Jenie ◽  
Evy Damayanthi ◽  
Irzaman Irzaman ◽  
Rimbawan Rimbawan ◽  
Dadang Sukandar ◽  
...  
Keyword(s):  
Neural Network ◽  
Clinical Trial ◽  
Artificial Neural Network ◽  
Fourier Transform ◽  
Blood Glucose ◽  
Discrete Fourier Transform ◽  
Glucose Measurement ◽  
Non Invasive ◽  
Artificial Neural

A prototype non-invasive blood glucose level measurement optical device (NI-BGL-MOD) has been developed. The NI-BGL-MOD uses a discrete Fourier transform (DFT) method and a fast artificial neural network algorithm to optimize device performance. The appropriate light-emitting diode for the sensory module was selected based on near-infrared spectrophotometry of a blood glucose model and human blood. DFT is implemented in an analog-to-digital converter module. An in vitro trial using the blood glucose model along with a clinical trial involving 110 participants were conducted to evaluate the performance of the prototype. The root-mean-square error of the prototype was 10.8 mg/dl in the in vitro trial and 3.64 mg/dl in the clinical trial, which is lower than the ISO-15197:2016 mandated value of 10 mg/dl. In each trial, consensus error grid analysis indicated that the measurement error was within the safe range. The sensitivity and specificity of the prototype were 0.83 (0.36, 1.00) and 0.90 (0.55, 1.00) in the in vitro trial and 0.81 (0.75, 0.85) and 0.83 (0.78, 0.87) in the clinical trial, respectively. In general, the proposed NI-BGL-MOD demonstrated good performance than gold-standard measurement. Key words: Non-invasive blood glucose measurement, optical device, discrete Fourier transform, multi-formulatric regression, fast artificial neural network

The use of neural network and discrete Fourier transform for real-time evaluation of friction stir welding

2011 ◽  
Vol 11 (8) ◽  
pp. 4839-4846 ◽  
Author(s):  
Enkhsaikhan Boldsaikhan ◽  
Edward M. Corwin ◽  
Antonette M. Logar ◽  
William J. Arbegast
Keyword(s):  
Neural Network ◽  
Fourier Transform ◽  
Friction Stir Welding ◽  
Real Time ◽  
Discrete Fourier Transform ◽  
Friction Stir ◽  
Time Evaluation

scholarly journals Effective Approach to Calculate Analysis Window in Infinite Discrete Gabor Transform

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Rui Li ◽  
Yong Huang ◽  
Jia-Bao Liu
Keyword(s):  
Fourier Transform ◽  
Computational Complexity ◽  
Linear Equation ◽  
Discrete Fourier Transform ◽  
Delta Function ◽  
Gabor Transform ◽  
Gabor Analysis ◽  
Analysis Window ◽  
Orthogonality Constraint ◽  
Infinite Sequences

The long-periodic/infinite discrete Gabor transform (DGT) is more effective than the periodic/finite one in many applications. In this paper, a fast and effective approach is presented to efficiently compute the Gabor analysis window for arbitrary given synthesis window in DGT of long-periodic/infinite sequences, in which the new orthogonality constraint between analysis window and synthesis window in DGT for long-periodic/infinite sequences is derived and proved to be equivalent to the completeness condition of the long-periodic/infinite DGT. By using the property of delta function, the original orthogonality can be expressed as a certain number of linear equation sets in both the critical sampling case and the oversampling case, which can be fast and efficiently calculated by fast discrete Fourier transform (FFT). The computational complexity of the proposed approach is analyzed and compared with that of the existing canonical algorithms. The numerical results indicate that the proposed approach is efficient and fast for computing Gabor analysis window in both the critical sampling case and the oversampling case in comparison to existing algorithms.

IMPORT LIBRARY DEVELOPMENT APPROACH FOR NEURAL NETWORKS IN NNEF FORMAT FOR OPENVX STANDARD

2018 ◽  
pp. 112-119
Author(s):  
K. V. Panfilova ◽  
D. V. Vorotnev ◽  
R. V. Golovanov ◽  
S. V. Umnyashkin ◽  
I. O. Sharonov
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Computational Complexity ◽  
Network Architecture ◽  
Low Computational Complexity ◽  
Low Level ◽  
Advantages And Disadvantages ◽  
End Point ◽  
Library Development ◽  
Development Approach

There are many frameworks for building, training and executing neural networks. Each of them offers their own format for storing network architecture. There are two frameworks considered in this paper: Caffe and Torch. They offer Google Protocol Buffer (protobuf) and the built-in Torch format for storing the architecture of neural networks. The existence of different formats leads to the difficulties of porting neural networks to finite devices of different manufacturers. It leads to difficulties in porting neural networks to end-point devices of different vendors. To resolve these issues the Khronos Group proposed universal NNEF format which will be mediator between frameworks and proprietary low-level libraries. The NNEF format allows storing a description of a neural network using a computational graph. In this paper the two main approaches of development of import (parsing) library for neural networks stored in NNEF: online and offline parsing. For each approach an advantages and disadvantages were noticed which will help developers to choose correct way of NNEF parser implementation. The main advantage of an offline parser is simplicity for debugging, and the online parser is a low computational complexity.

The Role of the Discrete Fourier Transform in the Contribution to Gear Transmission Error Spectra from Tooth-Spacing Errors

1987 ◽  
Vol 201 (3) ◽  
pp. 227-229 ◽  
Author(s):  
W D Mark
Keyword(s):  
Fourier Transform ◽  
Fourier Series ◽  
Error Analysis ◽  
Discrete Fourier Transform ◽  
Transmission Error ◽  
Spur Gear ◽  
Contact Ratio ◽  
Elastic Deformations ◽  
Exact Agreement

An expression is derived for the Fourier series spectrum of the transmission error arising from tooth-spacing errors on a single spur gear meshing with a perfect involute mating gear for the case of a contact ratio of unity and no elastic deformations present. This expression is found to be in exact agreement with previously derived results. The expression illustrates the role of the discrete Fourier transform in transmission error analysis and interpretation.

Sign in / Sign up

Export Citation Format

Share Document