Relations Between Microscopic and Mesoscopic Levels Shown by Calculating Pulse Probability Conditional on EEG Amplitude, Giving the Asymmetric Sigmoid Function

2000 ◽  
pp. 241-264 ◽  
Author(s):  
Walter J. Freeman
Keyword(s):  
Sigmoid Function

S-CCCapsule: Pneumonia detection in chest X-ray images using skip-connected convolutions and capsule neural network

2021 ◽  
pp. 1-25
Author(s):  
Kwabena Adu ◽  
Yongbin Yu ◽  
Jingye Cai ◽  
Victor Dela Tattrah ◽  
James Adu Ansere ◽  
...  
Keyword(s):  
Neural Network ◽  
Human Error ◽  
Medical Center ◽  
Confusion Matrix ◽  
Area Under The Curve ◽  
Dynamic Routing ◽  
Sigmoid Function ◽  
Radiological Society ◽  
Chest X Ray ◽  
Sensitivity Specificity

The squash function in capsule networks (CapsNets) dynamic routing is less capable of performing discrimination of non-informative capsules which leads to abnormal activation value distribution of capsules. In this paper, we propose vertical squash (VSquash) to improve the original squash by preventing the activation values of capsules in the primary capsule layer to shrink non-informative capsules, promote discriminative capsules and avoid high information sensitivity. Furthermore, a new neural network, (i) skip-connected convolutional capsule (S-CCCapsule), (ii) Integrated skip-connected convolutional capsules (ISCC) and (iii) Ensemble skip-connected convolutional capsules (ESCC) based on CapsNets are presented where the VSquash is applied in the dynamic routing. In order to achieve uniform distribution of coupling coefficient of probabilities between capsules, we use the Sigmoid function rather than Softmax function. Experiments on Guangzhou Women and Children’s Medical Center (GWCMC), Radiological Society of North America (RSNA) and Mendeley CXR Pneumonia datasets were performed to validate the effectiveness of our proposed methods. We found that our proposed methods produce better accuracy compared to other methods based on model evaluation metrics such as confusion matrix, sensitivity, specificity and Area under the curve (AUC). Our method for pneumonia detection performs better than practicing radiologists. It minimizes human error and reduces diagnosis time.

scholarly journals Blind Deblurring Based on Sigmoid Function

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3484
Author(s):  
Shuhan Sun ◽  
Lizhen Duan ◽  
Zhiyong Xu ◽  
Jianlin Zhang
Keyword(s):  
Performance Optimization ◽  
Degradation Process ◽  
Image Deconvolution ◽  
Sigmoid Function ◽  
Blind Image Deblurring ◽  
Linear Estimators ◽  
Blind Deblurring ◽  
Degraded Image ◽  
Excellent Property ◽  
Blind Image

Blind image deblurring, also known as blind image deconvolution, is a long-standing challenge in the field of image processing and low-level vision. To restore a clear version of a severely degraded image, this paper proposes a blind deblurring algorithm based on the sigmoid function, which constructs novel blind deblurring estimators for both the original image and the degradation process by exploring the excellent property of sigmoid function and considering image derivative constraints. Owing to these symmetric and non-linear estimators of low computation complexity, high-quality images can be obtained by the algorithm. The algorithm is also extended to image sequences. The sigmoid function enables the proposed algorithm to achieve state-of-the-art performance in various scenarios, including natural, text, face, and low-illumination images. Furthermore, the method can be extended naturally to non-uniform deblurring. Quantitative and qualitative experimental evaluations indicate that the algorithm can remove the blur effect and improve the image quality of actual and simulated images. Finally, the use of sigmoid function provides a new approach to algorithm performance optimization in the field of image restoration.

A new reaching law for sliding mode observer of controllable excitation linear synchronous motor

2021 ◽  
pp. 014233122110320
Author(s):  
Xiaolei Shi ◽  
Yipeng Lan ◽  
Yunpeng Sun ◽  
Cheng Lei
Keyword(s):  
Sliding Mode ◽  
Dynamic Performance ◽  
Angular Position ◽  
Lyapunov Stability Theory ◽  
Synchronous Motor ◽  
Position Estimation ◽  
Sliding Mode Observer ◽  
Sigmoid Function ◽  
Reaching Law ◽  
Linear Synchronous Motor

This paper presents a sliding mode observer (SMO) with new reaching law (NRL) for observing the real-time linear speed of a controllable excitation linear synchronous motor (CELSM). For the purpose of balancing the dilemma between the rapidity requirement of dynamic performance and the chattering reduction on sliding mode surface, the proposed SMO with NRL optimizes the reaching way of the conventional constant rate reaching law (CRRL) to the sliding mode surface by connecting the reaching process with system states and the sliding mode surface. The NRL is based on sigmoid function and power function, with proper options of exponential term and power term, the NRL is capable of eliminating the effect of chattering on accuracy of the angular position estimation and speed estimation. Compared with conventional CRRL, the SMO with NRL achieves suppressing the chattering phenomenon and tracking the transient process rapidly and accurately. The stability analysis is given to prove the convergence of the SMO through the Lyapunov stability theory. Simulation and experimental results show the effectiveness of the proposed NRL method.

scholarly journals In Situ Shear Test for Revealing the Mechanical Properties of the Gravelly Slip Zone Soil

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6531 ◽  
Author(s):  
Zongxing Zou ◽  
Qi Zhang ◽  
Chengren Xiong ◽  
Huiming Tang ◽  
Lei Fan ◽  
...  
Keyword(s):  
Mechanical Property ◽  
Plastic Deformation ◽  
Shear Test ◽  
Slip Zone ◽  
Three Gorges Reservoir Area ◽  
Silty Clay ◽  
Sigmoid Function ◽  
In Situ Test ◽  
Deformation Stage

Slip zone soil is usually composed of clay or silty clay; in some special geological environments, it contains gravels, which make the properties of the slip zone soil more complex. Unfortunately, in many indoor shear tests, gravels are removed to meet the demands of apparatus size, and the in situ mechanical property of the gravelly slip zone soil is rarely studied. In this study, the shear mechanical property of the gravelly slip zone soil of Huangtupo landslide in the Three Gorges Reservoir area of China was investigated by the in situ shear test. The test results show that the shear deformation process of the gravelly slip zone soil includes an elastic deformation stage, elastic–plastic deformation stage, and plastic deformation stage. Four functions were introduced to express the shear constitutive model of the gravelly slip zone soil, and the asymmetric sigmoid function was demonstrated to be the optimum one to describe the relationship of the shear stress and shear displacement with a correlation coefficient of 0.986. The comparison between the in situ test and indoor direct shear test indicates that gravels increase the strength of the slip zone soil. Therefore, the shear strength parameters of the gravelly slip zone soil obtained by the in situ test are more preferable for evaluating the stability of the landslide and designing the anti-slide structures.

The Modelling of Hysteresis in Magnetorheological Dampers Using a Generalised Prandtl-Ishlinskii Approach

2010 ◽  
Author(s):  
Kun Wang ◽  
Ying Zhang ◽  
Richard W. Jones
Keyword(s):  
Mr Damper ◽  
Control Analysis ◽  
Sigmoid Function ◽  
Magnetorheological Dampers ◽  
Operating Characteristics ◽  
Major Drawback ◽  
Analysis And Design ◽  
Force Velocity ◽  
Play Operator ◽  
Fidelity Model

The major drawback of magnetorheological dampers (MR) lies in their non-linear and hysteretic force-velocity response. To take full advantage of the operating characteristics of these devices a high fidelity model is required for control analysis and design. In this contribution the ability of a generalised PI operator-based model to represent the characteristics of a commercially available MR damper is examined. This approach allows the user to define the PI operator to best match the hysteresis characteristics. For the MR damper the force-velcoity hysteresis characteristic is ‘S’ shaped and constrained. Two possibilities will be examined here for the generalised play operator; an hyperbolic tan function and a symmetric sigmoid function.

scholarly journals A Site Amplification Model for Crustal Earthquakes

Geosciences ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. 264 ◽  
Author(s):  
M. Sandıkkaya ◽  
L. Dinsever
Keyword(s):  
Soft Soil ◽  
Correlation Coefficients ◽  
Nonlinear Effects ◽  
Site Amplification ◽  
Sigmoid Function ◽  
Deep Soil ◽  
Soil Stiffness ◽  
Site Model ◽  
Soil Nonlinearity ◽  
Crustal Earthquakes

A global dataset which is composed of more than 20,000 records is used to develop an empirical nonlinear soil amplification model for crustal earthquakes. The model also includes the deep soil effect. The soil nonlinearity is formulated in terms of input rock motion and soil stiffness. The input rock motion is defined by the pseudo-spectral acceleration at rock site condition (PSArock) which is also modified with between-event residual. Application of PSArock simplifies the usage of the site model by diminishing the need of using the period-dependent correlation coefficients in hazard studies. The soil stiffness is expressed by a Gompertz sigmoid function which restricts the nonlinear effects at both of the very soft soil sites and very stiff soil sites. In order to surpass the effect of low magnitude and long-distant recordings on soil nonlinearity, the nonlinear site coefficients are constrained by using a limited dataset. The coefficients of linear site scaling and deep soil effect are obtained with the full database. The period average of site-variability is found to be 0.43. The sigma decreases with decreasing the soil stiffness or increasing input rock motion. After employing residual analysis, the region-dependent correction coefficients for linear site scaling are also obtained.

scholarly journals Levenberg-Marquardt Algorithm Combined with Bipolar Sigmoid Function to Measure Open Unemployment Rate in Indonesia

2018 ◽  
Author(s):  
Anjar Wanto ◽  
Irfan Sudahri Damanik ◽  
Indra Gunawan ◽  
Eka Irawan ◽  
Heru Satria Tambunan ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Unemployment Rate ◽  
Sigmoid Function ◽  
Marquardt Algorithm ◽  
Testing Data ◽  
Levenberg Marquardt ◽  
Unemployment Data ◽  
The Republic ◽  
The Government ◽  
Two Stages

The purpose of this research is to see how much open unemployment rate according to the highest education completed in the country of Indonesia for subsequent years through predictions used on the basis of existing data, which later as input for the government so that the government can make better policies to suppress the unemployment rate. This research uses artificial neural network application using a combination of Levenberg-Marquardt Algorithm with bipolar sigmoid function. Open unemployment data according to the highest education is sourced from the National Labor Force Survey of the Republic of Indonesia, 2013-2017 in each semester. The data processing consists of two stages where the first phase of pattern recognition and the second stage is predicted. Pattern recognition and prediction use different data from the same process that uses data training and data testing. Data Training year 2013-2015 with a target of 2016, while data testing year 2014-2016 with the target year 2017. Architectural model used there are five, among others 6-2-5-2, 6-5-6-2, 6- 5-8-2, 6-5-10-2 and 6-8-12-2. From the 5 models, it can be concluded that the best model is 6-5-10-2 with the epoch of 13 iterations, MSE in February 0.0109696004, MSE in August 0.0233797200. While the accuracy rate in February and August is the same, that is equal to 88%.

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