Signal filtering using hard-limited digital processing. Part 1: General description and performance with white-noise background

1970 ◽  
Vol 117 (9) ◽  
pp. 1767
Author(s):  
J.H. Blythe ◽  
K. Edgcombe ◽  
A. Ryley ◽  
W.D. Worthy
Keyword(s):  
White Noise ◽  
Digital Processing ◽  
General Description ◽  
Signal Filtering ◽  
Noise Background ◽  
And Performance ◽  
White Noise Background

scholarly journals Wavelet Co-movement Significance Testing with Respect to Gaussian White Noise Background

2018 ◽  
Vol 16 ◽  
pp. 01002
Author(s):  
Jitka Poměnková ◽  
Eva Klejmová ◽  
Tobiáš Malach
Keyword(s):  
White Noise ◽  
Gaussian White Noise ◽  
Real Data ◽  
Significance Testing ◽  
Noise Background ◽  
Advantages And Disadvantages ◽  
The United Kingdom ◽  
Long Run ◽  
Short Run ◽  
White Noise Background

The paper deals with significance testing of time series co-movement measured via wavelet analysis, namely via the wavelet cross-spectra. This technique is very popular for its better time resolution compare to other techniques. Such approach put in evidence the existence of both long-run and short-run co-movement. In order to have better predictive power it is suitable to support and validate obtained results via some testing approach. We investigate the test of wavelet power cross-spectrum with respect to the Gaussian white noise background with the use of the Bessel function. Our experiment is performed on real data, i.e. seasonally adjusted quarterly data of gross domestic product of the United Kingdom, Korea and G7 countries. To validate the test results we perform Monte Carlo simulation. We describe the advantages and disadvantages of both approaches and formulate recommendations for its using.

scholarly journals White Noise Background Improves Tone Discrimination by Suppressing Cortical Tuning Curves

Cell Reports ◽  
2019 ◽  
Vol 29 (7) ◽  
pp. 2041-2053.e4 ◽  
Author(s):  
Rasmus Kordt Christensen ◽  
Henrik Lindén ◽  
Mari Nakamura ◽  
Tania Rinaldi Barkat
Keyword(s):  
White Noise ◽  
Noise Background ◽  
Tuning Curves ◽  
White Noise Background ◽  
Tone Discrimination

scholarly journals Design and Performance Improvement of CNTFET Based Content Addressable Memory (CAM) Cells

2019 ◽  
Vol 9 (1) ◽  
pp. 1694-1698
Keyword(s):  
Performance Improvement ◽  
Power Analysis ◽  
Electronic Device ◽  
Digital Processing ◽  
Basic Component ◽  
Content Addressable Memory ◽  
Innovative Methods ◽  
Scaling Down ◽  
And Performance ◽  
Carbon Nano Tube

The scaling down of transistors is of paramount importance to make ICs and devices more portable and efficient. As it is the most basic component of every electronic device, there is need of finding better and innovative methods of transistor characterization. CNTFET has shown the promise and is best suited for today’s faster digital processing units and Memory devices. Here Carbon Nano Tube (CNT) is characterized for its electrical property and then designed a XOR based CAM cell using CNTFET. Both delay and power analysis for the designed CAM is done.

Influence of Poisson White Noise on the Response Statistics of Nonlinear System and Its Applications to Bearing Fault Diagnosis

2019 ◽  
Vol 14 (3) ◽  
Author(s):  
Dawen Huang ◽  
Jianhua Yang ◽  
Dengji Zhou ◽  
Grzegorz Litak ◽  
Houguang Liu
Keyword(s):  
Nonlinear System ◽  
White Noise ◽  
Noise Intensity ◽  
Arrival Rate ◽  
Scale Transformation ◽  
Poisson White Noise ◽  
Noise Background ◽  
Bearing Fault ◽  
Fault Features ◽  
Bearing Structure

In view of complex noise background in engineering practices, this paper presents a rescaled method to detect failure features of bearing structure in the Poisson white noise background. To realize the scale transformation of the fault signal with Poisson white noise, a general scale transformation (GST) method is introduced based on the second-order underdamped nonlinear system. The signal features are successfully extracted through the proposed rescaled method in the simulated and experimental cases. We focus on the influence of Poisson white noise parameters and damping coefficient on the response of nonlinear system. The impulse arrival rate and noise intensity have opposite effects on the realization of stochastic resonance (SR) and the extraction of bearing fault features. Poisson white noise with smaller impulse arrival rate or larger noise intensity is easier to induce SR to extract bearing fault features. The optimal matching between the nonlinear system and the input signal is formed by the optimization algorithm, which greatly improves the extraction efficiency of fault features. Compared with the normalized scale transformation (NST) method, the GST has significant advantages in recognizing the bearing structure failure. The differences and connections between Poisson white noise and Gaussian white noise are discussed in the rescaled system excited by the experiment signal. This paper might provide several practical values for recognizing bearing fault mode in the Poisson white noise.

Spot Locator for Autonomous Parking

2009 ◽  
Author(s):  
Nikolai Moshchuk ◽  
Shih-Ken Chen
Keyword(s):  
Position Estimation ◽  
Ultrasonic Sensors ◽  
Test Vehicle ◽  
Detection Range ◽  
Signal Filtering ◽  
Suggested Algorithm ◽  
Parking Spot ◽  
Vehicle Position ◽  
And Performance ◽  
Left Front

For a semi-autonomous or fully-autonomous parking system, detecting adequate parking spot is the first step. Ultrasonic sensor possesses a good compromise between cost and performance since the detection range is very small. This paper describes a parking assist system with two ultrasonic sensors mounted at the left front and right front corners of the vehicle. Special signal filtering and processing is derived. Kinematic observer for the vehicle position estimation during search and parking phases is discussed. The suggested algorithm is implemented in Matlab/Simulink and was verified in a test vehicle.

The choice of the sampling frequency and optimal method of signal digital processing in the problems considering random loading process for assessing durability

2019 ◽  
Vol 85 (7) ◽  
pp. 64-72 ◽  
Author(s):  
Irina V. Gadolina ◽  
Natalia G. Lisachenko ◽  
Yuriy A. Svirskiy ◽  
Dmitry A. Dubin
Keyword(s):  
Random Process ◽  
Extreme Values ◽  
Optimal Algorithm ◽  
Digital Processing ◽  
Digital Information ◽  
Random Loading ◽  
Optimal Method ◽  
Strength Assessment ◽  
And Performance ◽  
Selection Of

Theoretical and practical issues of processing digital information in the problems related to durability assessment in conditions of loading are considered. Due to the specifics of the problem, in which the precise dedermination of the extreme values and their sequence is of primary importance, a number of generally accepted recommendations appeared invalid. For example, the Kotelnikov theorem, which was originally proposed in relation to the problems of estimating the frequency composition of the process, can lead to significant errors. It is shown that the requirements to the analysis of random loading processes with a goal of further assessment of the durability, due to their specificity, contradict with the specified requirements, namely, when choosing a frequency according to this rule, an error can be made, and not to the margin of the strength assessment. We considered the issue regarding digital filtering of hardware overshoots. Alternative approaches to the selection of extrema of the random process are analyzed: 1) direct hardware selection of extrema and 2) discretization by the method of level crossings. The latter approach has an optimal algorithm for isolating extremes and makes it possible to isolate extremes of a random process with lower costs and greater accuracy. The natural transition to integer arithmetic provides further optimization of the algorithm. The model and real examples demonstrate gains in terms of speed and memory, which ultimately promote an increase in the reliability of the information required for assessing the durability. The savings in memory and performance will allow processing of long-term implementations and result in a more accurate estimating of the remaining life and durability at the stage of production.

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