scholarly journals Nonconvex Energy Minimization with Unsupervised Line Process Classifier for Efficient Piecewise Constant Signals Reconstruction

2021 ◽  
Vol 9 (2) ◽  
pp. 435-452
Author(s):  
Anass Belcaid ◽  
Mohammed Douimi
Keyword(s):  
Process Model ◽  
Least Square ◽  
Piecewise Constant ◽  
Step Detection ◽  
Second Stage ◽  
Human Activity Analysis ◽  
Nonconvex Energy ◽  
Line Process ◽  
Least Square Problem ◽  
Detection Quality

In this paper, we focus on the problem of signal smoothing and step-detection for piecewise constant signals. This problem is central to several applications such as human activity analysis, speech or image analysis, and anomaly detection in genetics. We present a two-stage approach to minimize the well-known line process model which arises from the probabilistic representation of the signal and its segmentation. In the first stage, we minimize a TV least square problem to detect the majority of the continuous edges. In the second stage, we apply a combinatorial algorithm to filter all false jumps introduced by the TV solution. The performances of the proposed method were tested on several synthetic examples. In comparison to recent step-preserving denoising algorithms, the acceleration presents a superior speed and competitive step-detection quality.

A Novel Online Change Point Detection Using an Approximate Random Blanket and the Line Process Energy

2020 ◽  
Vol 29 (06) ◽  
pp. 2050018
Author(s):  
A. Belcaid ◽  
M. Douimi
Keyword(s):  
Change Point ◽  
Activation Function ◽  
Change Point Detection ◽  
Piecewise Constant ◽  
Markov Random ◽  
Human Activity Analysis ◽  
Noisy Observation ◽  
Line Process ◽  
Process Energy ◽  
Point Detection

In this paper, we focus on the problem of change point detection in piecewise constant signals. This problem is central to several applications such as human activity analysis, speech or image analysis and anomaly detection in genetics. We present a novel window-sliding algorithm for an online change point detection. The proposed approach considers a local blanket of a global Markov Random Field (MRF) representing the signal and its noisy observation. For each window, we define and solve the local energy minimization problem to deduce the gradient on each edge of the MRF graph. The gradient is then processed by an activation function to filter the weak features and produce the final jumps. We demonstrate the effectiveness of our method by comparing its running time and several detection metrics with state of the art algorithms.

On-line process-model-based control of a plasma etcher

1992 ◽  
Author(s):  
Michael E. Parten ◽  
R. R. Rhinehart ◽  
Vikram Singh
Keyword(s):  
Process Model ◽  
Model Based Control ◽  
Model Based ◽  
On Line ◽  
Line Process

Intelligent Control of Flocculation Process Based on Radial Basis Probabilistic Neural Network for Sewage Treatment

2010 ◽  
Vol 44-47 ◽  
pp. 3289-3293
Author(s):  
Jing Wen Tian ◽  
Mei Juan Gao
Keyword(s):  
Neural Network ◽  
Control System ◽  
Process Model ◽  
Probabilistic Neural Network ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Least Square ◽  
Radial Basis ◽  
Flocculation Process

The flocculating process of sewage treatment is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The radial basis probabilistic neural network (RBPNN) has the ability of strong function approach and fast convergence. In this paper, an intelligent optimized control system based on radial basis probabilistic neural network is presented. We constructed the structure of radial basis probabilistic neural network that used for controlling the flocculation process, and adopt the K-Nearest Neighbor algorithm and least square method to train the network. We given the architecture of control system and analyzed the working process of system. In this system, the parameters of flocculation process were measured using sensors, and then the control system can control the flocculation process real-time. The system was used in the sewage treatment plant. The experimental results prove that this system is feasible.

scholarly journals Numerical method to a class of boundary value problems

2018 ◽  
Vol 22 (4) ◽  
pp. 1877-1883 ◽  
Author(s):  
Yu-Yang Qiu
Keyword(s):  
Boundary Value Problems ◽  
Numerical Method ◽  
Conjugate Gradient ◽  
Iteration Method ◽  
Boundary Value ◽  
Solution Process ◽  
Least Square ◽  
Least Square Problem ◽  
Matrix Iteration

A class of boundary value problems can be transformed uniformly to a least square problem with Toeplitz constraint. Conjugate gradient least square, a matrix iteration method, is adopted to solve this problem, and the solution process is elucidated step by step so that the example can be used as a paradigm for other applications.

Study on Process Planning of Auto Body Welding Line Based on Digital Factory

2012 ◽  
Vol 562-564 ◽  
pp. 639-642
Author(s):  
Sheng Fang Zhang ◽  
Yong Quan Gan ◽  
Kui Zeng ◽  
Chang Jun Ji
Keyword(s):  
Process Planning ◽  
Process Model ◽  
Welding Process ◽  
Planning System ◽  
Production Cycle ◽  
Digital Factory ◽  
Process Planning System ◽  
Welding Line ◽  
Line Process ◽  
Auto Body

Auto body welding line process planning is one of the key sections which determines the production cycle of the whole automobile. Take the advanced digital factory software – Process Designer as developing platform, the production information management and the process planning of the auto body welding line are realized by creating manufacturing model and process model, and the auto body welding line process planning system is constructed, the realizing method and step of processing planning are described in detail. Furthermore, take one auto body floor welding line as an example, the 3D digital factory based on the process planning system is generated, and the planning results is verified. The result shows, applying the system in welding process planning, can shorten the time and increase the accuracy of process planning remarkably.

Sign in / Sign up

Export Citation Format

Share Document