scholarly journals Adaptive Stochastic Filtration Based on the Estimation of the Covariance Matrix of Measurement Noises Using Irregular Accurate Observations

Inventions ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 10
Author(s):  
Sergey Sokolov ◽  
Arthur Novikov ◽  
Marianna Polyakova
Keyword(s):  
Covariance Matrix ◽  
Adaptive Estimation ◽  
Observation System ◽  
Mobile Object ◽  
New Approach ◽  
Measurement Systems ◽  
System Parameters ◽  
Traditional Scheme ◽  
Adaptive Filtration ◽  
Measurement Noises

In measurement systems operating under various disturbances the probabilistic characteristics of measurement noises are usually known approximately. To improve the observation accuracy, a new approach to the Kalman’s filter adaptation is proposed. In this approach, the Covariance Matrix of Measurement Noises (CMMN) is estimated by accurate measurements detected irregularly by the mobile object observation system (from radiofrequency identifiers, etalon reference, fixed points etc.). The problem of adaptive estimation of the observer’s noises covariance matrix in the Kalman filter is solved analytically for two cases: mutual noises correlation, and its absence. The numerical example for adaptive filtration of complexing navigation system parameters of a mobile object using irregular accurate measurements is given to illustrate the effectiveness of the proposed algorithm. Coordinate estimating errors have changed in comparison with the traditional scheme from 100 m to 2 m in latitude, and from 200 m to 1.5 m in longitude.

scholarly journals An Efficient Method of Image Encryption Using Rossler Chaotic System

2021 ◽  
Vol 10 (2) ◽  
pp. 11
Author(s):  
Yasir Ahmed Hamza ◽  
Marwan Dahar Omer
Keyword(s):  
Image Encryption ◽  
Chaotic System ◽  
Initial Conditions ◽  
Computation Time ◽  
Encryption Algorithm ◽  
Brute Force ◽  
Symmetric Encryption ◽  
New Approach ◽  
System Parameters ◽  
Plain Image

In this study, a new approach of image encryption has been proposed. This method is depends on the symmetric encryption algorithm RC4 and Rossler chaotic system. Firstly, the encryption key is employed to ciphering a plain image using RC4 and obtains a ciphered-image. Then, the same key is used to generate the initial conditions of the Rossler system. The system parameters and the initial conditions are used as the inputs for Rossler chaotic system to generate the 2-dimensional array of random values. The resulted array is XORed with the ciphered-image to obtain the final encrypted-image. Based on the experimental results, the proposed method has achieved high security and less computation time. Also, the proposed method can be resisted attacks like (statistical, brute-force, and differential).

Sensor and Actuator Intrusion Detection for Cyber-Physical Systems via Adaptive Estimation Algorithm

2020 ◽  
Author(s):  
Jiayi Su ◽  
Yuqin Weng ◽  
Susan C. Schneider ◽  
Edwin E. Yaz
Keyword(s):  
Kalman Filters ◽  
Adaptive Estimation ◽  
Estimation Algorithm ◽  
Cyber Physical Systems ◽  
Motor Speed ◽  
New Approach ◽  
Physical Systems ◽  
Unknown Type ◽  
Different Types ◽  
Conditional State

Abstract In this work, a new approach to detect sensor and actuator intrusion for Cyber-Physical Systems using a bank of Kalman filters is presented. The case where the unknown type of the intrusion signal is considered first, using two Kalman filters in a bank to provide the conditional state estimates, then the unknown type of intrusion signal can be detected properly via the adaptive estimation algorithm. The case where the target (either sensor or actuator) of the intrusion signal is unknown is also considered, using four Kalman filters in a bank designed to detect if the intrusion signal is about to affect healthy sensor or actuator signal. To test these methods, a DC motor speed control system subject to attack by different types of sensor and actuator signals is simulated. Simulations show that different types of sensor and actuator intrusion signals can be detected properly without the knowledge of the nature and the type of these signals.

The New Approach to Electromagnetic Fields Interpretation for TEM with Areal Observation System

2001 ◽  
Author(s):  
G.M. Trigubovich ◽  
M.E. Royak ◽  
Y.G. Soloveichik ◽  
A.V. Chernyshev
Keyword(s):  
Electromagnetic Fields ◽  
Observation System ◽  
New Approach

A new approach for mobile and expandable real-time deep seafloor observation - adaptable observation system

2002 ◽  
Vol 27 (2) ◽  
pp. 182-192 ◽  
Author(s):  
K. Kawaguchi ◽  
K. Hirata ◽  
T. Nishida ◽  
S. Obana ◽  
H. Mikada
Keyword(s):  
Real Time ◽  
Observation System ◽  
New Approach ◽  
Seafloor Observation

Error estimates for inverse modeling schemes using seismic traveltimes

Geophysics ◽  
1981 ◽  
Vol 46 (9) ◽  
pp. 1227-1234 ◽  
Author(s):  
Bjørn Ursin
Keyword(s):  
Covariance Matrix ◽  
Impulse Response ◽  
Additive White Gaussian Noise ◽  
Information Matrix ◽  
Measurement Data ◽  
Confidence Regions ◽  
Measurement Systems ◽  
Estimated Parameters ◽  
Layer Velocity ◽  
Seismic Measurement

Different methods for estimating parameters in a layered geologic model are discussed. Traveltime parameters, estimated from seismic data, are used to estimate the layer parameters defining the velocity function in each layer and the interfaces between the layers. Seismic measurement data are assumed to consist of a sum of nonoverlapping reflected pulses and additive white Gaussian noise. An estimate of the covariance of the traveltime parameters is then given by the inverse of Fischer’s information matrix. It is shown how the information matrix can be computed theoretically or directly from data. Expressions for the covariance matrix of the layer parameters are given. The results can be used to compute confidence regions for the estimated parameters. Optimal seismic measurement systems are discussed, resulting in a criterion for designing an optimal seismic pulse: The energy of the derivative of the received signal (the source pulse convolved with the impulse response of the earth and the impulse response of the instruments) should be maximized. Parameter estimation in a horizontally layered model is considered as an example, and the covariance matrix of the layer velocity and layer thickness is given explicitly.

scholarly journals Novelty detection-based approach for Alzheimer’s disease and mild cognitive impairment diagnosis from EEG

2021 ◽  
Author(s):  
Matous Cejnek ◽  
Oldrich Vysata ◽  
Martin Valis ◽  
Ivo Bukovsky
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Novelty Detection ◽  
Disease Diagnosis ◽  
Eeg Signal ◽  
New Approach ◽  
Activity Assessment ◽  
Adaptive Filtration

AbstractAlzheimer’s disease is diagnosed via means of daily activity assessment. The EEG recording evaluation is a supporting tool that can assist the practitioner to recognize the illness, especially in the early stages. This paper presents a new approach for detecting Alzheimer’s disease and potentially mild cognitive impairment according to the measured EEG records. The proposed method evaluates the amount of novelty in the EEG signal as a feature for EEG record classification. The novelty is measured from the parameters of EEG signal adaptive filtration. A linear neuron with gradient descent adaptation was used as the filter in predictive settings. The extracted feature (novelty measure) is later classified to obtain Alzheimer’s disease diagnosis. The proposed approach was cross-validated on a dataset containing EEG records of 59 patients suffering from Alzheimer’s disease; seven patients with mild cognitive impairment (MCI) and 102 controls. The results of cross-validation yield 90.73% specificity and 89.51% sensitivity. The proposed method of feature extraction from EEG is completely new and can be used with any classifier for the diagnosis of Alzheimer’s disease from EEG records.

A New Approach for GNSS Ambiguity Decorrelation

2011 ◽  
Vol 403-408 ◽  
pp. 1968-1971 ◽  
Author(s):  
Qiu Zhao Zhang ◽  
Shu Bi Zhang ◽  
Wan Li Liu
Keyword(s):  
Covariance Matrix ◽  
Cholesky Decomposition ◽  
Satellite System ◽  
Integer Ambiguity ◽  
Integer Matrix ◽  
New Approach ◽  
Ambiguity Decorrelation ◽  
Global Navigation Satellite ◽  
Carrier Phase Ambiguity ◽  
Gauss Transformation

Integer carrier phase ambiguity resolution is the key to fast and high-precision Global navigation satellite system(GNSS) positioning and application. LAMBDA method is one of the best methods for fixing integer ambiguity. The principle of LAMBDA is discussed. For incompleteness of Cholesky decomposition and complexity of Integer Gauss transformation, a new approach for GNSS ambiguity decorrelation is proposed based on symmetric pivoting strategy and united inverse integer strategy. The new algorithm applies symmetric pivoting strategy to ambiguity covariance matrix while doing Cholesky decomposition, then finds the inverse and integer matrix of ‘L’. This method not only uses Cholesky decomposition to improve efficiency, but also avoids complicated Integer Gauss transformations. The feasibility and advantage of the method are verified using randomly simulation covariance matrix.

Towards the Realization of a Conveyor Platform for Microparts Employing a Deformable Surface

2012 ◽  
Author(s):  
Mohsin Rizwan ◽  
Panos S. Shiakolas
Keyword(s):  
Initial Velocity ◽  
Active Surface ◽  
Automatic Assembly ◽  
Input Frequency ◽  
New Approach ◽  
System Parameters ◽  
Operational Characteristics ◽  
Continuous Surface ◽  
System Output ◽  
Actuator System

Various approaches ranging from micro-sized air-nozzles to direct manipulation through bimetallic actuators have been proposed to displace/orient sub-millimeter sized parts for automatic assembly of homogeneous and/or heterogeneous microdevices Keeping in view the micromanipulation requirements, based on the concept of active surface, a new approach for micromanipulation has been proposed by the authors which comprises of controlled deformation of a flexible continuous surface [1]. A single actuator system has limited micropart translocation capability and multiple sequential actuators need to be used if the required translocation distance is more than the capability of an actuator. For a single actuator system, the parameters of the system and their influence on the system output (translocation distance or travel distance) have already been discussed as function of the input frequency, actuator stroke, surface roughness and deformation wavelength [2]. In a multiactuator system, the subsequent actuators engage the micropart with a finite initial velocity and at some position relative to the actuator. Therefore, a sequential array of actuators exhibits a different set of overall operational characteristics. This manuscript describes the operational characteristics of sequential actuators towards a microconveyor system over a range of actuator frequencies and other system parameters and estimates the system output i.e. the micropart distance travelled or translocation. The discussion is based on a two actuator system with the conclusions generalized for a multi-actuator system.

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