Detection of spread-spectrum signals using the time-domain filtered cross spectral density

1995 ◽  
Vol 142 (6) ◽  
pp. 286 ◽  
Author(s):  
A.W. Houghton
Keyword(s):  
Spectral Density ◽  
Time Domain ◽  
Spread Spectrum ◽  
Cross Spectral Density ◽  
The Time Domain ◽  
Spread Spectrum Signals

A Novel Algorithm for Long Pseudo-Code Acquisition in Spread Spectrum Communication System

2014 ◽  
Vol 610 ◽  
pp. 905-909
Author(s):  
Chun Hui Ren ◽  
Zhong Quan He
Keyword(s):  
Time Domain ◽  
Spread Spectrum ◽  
Communication System ◽  
Binary Search ◽  
Spread Spectrum Communication ◽  
Specific Method ◽  
Capture Time ◽  
Reference Sequences ◽  
The Time Domain ◽  
Novel Algorithm

The capture of long Pseudo-Code code is the most important technology in spread spectrum system. we use XFAST,AVERAGE to solve this problem in old days. A new algorithm is proposed which based on the time domain samples and binary search according the autocorrelation of the Pseudo-Code (PN code) and improve the speed of the capture of long Pseudo-Code code in spread spectrum system. Firstly, received spread spectrum signal's simple rate is reduced to a quarter of the chip rate and determine with a specific method, then divide the local PN code into four parts and accumulated to a new sequence. finally, the synchronous pseudo-code is captured with the correlation of the two new reference sequences. Compared with conventional methods such as XFAST, capture time and precision are improved.

scholarly journals Time-resolving the COVID-19 outbreak using frequency domain analysis

2020 ◽  
Author(s):  
Keno L. Krewer ◽  
Mischa Bonn
Keyword(s):  
Steady State ◽  
Severe Acute Respiratory Syndrome ◽  
Spectral Density ◽  
Frequency Domain ◽  
Time Domain ◽  
Case Fatality ◽  
Frequency Domain Analysis ◽  
Time Domain Data ◽  
Current Outbreak ◽  
The Time Domain

AbstractDifficulties assessing and predicting the current outbreak of the severe acute respiratory syndrome coronavirus 2 can be traced, in part, to the limitations of a static description of a dynamic system. Fourier transforming the time-domain data of infections and fatalities into the frequency domain makes the dynamics easily accessible. Defining a quantity like the “case fatality” as a spectral density allows a more sensible comparison between different countries and demographics during an ongoing outbreak. Such a case fatality informs not only how many of the confirmed cases end up as fatalities, but also when. For COVID-19, knowing this time and using the entire case fatality spectrum allows determining that an outbreak had entered a steady-state (most likely its end) about 14 days before this is obvious from time-domain data. The lag between confirmations and deaths also helps to estimate the effectiveness of contact management: The larger the lag, the less time the average confirmed person had to infect people before quarantine.

Research on the Dynamic Characteristic of the Bogie in Dynamic Track Stabilizer under the Excitation of the Track Irregularities

2012 ◽  
Vol 178-181 ◽  
pp. 1438-1441
Author(s):  
Li Hua Wang ◽  
Guang Wei Liu ◽  
An Ning Huang ◽  
Ya Yu Huang
Keyword(s):  
Spectral Density ◽  
Dynamic Characteristic ◽  
Time Domain ◽  
Large Scale ◽  
Degree Of Freedom ◽  
Speed Up ◽  
Critical Components ◽  
The Time Domain ◽  
Six Degree Of Freedom ◽  
Track Irregularities

With the large-scale speed-up of the railway, the dynamic track stabilizer will play an important role on the track overhauling and railroading of new line in our country. Bogie is one of the major critical components of the dynamic track stabilizer; its vibrating characteristic will affect the vibrating characteristic of the dynamic track stabilizer directly. The method of numerical simulate was used, based on the spectral density of the track irregularities, the time domain loads of the track irregularities were gained. Then the vibrating characteristics of the dynamic track stabilizer bogie under the excitation of the track irregularities were analyzed on the bases of the ANSYS/LS-DYNA. And the lateral, dilation, ups and downs, nod, swing and anti-rolling vibrating characteristics of the bogie on the six degree of freedom were obtained. The analysis results of this paper will provide foundation for the research on the stationarity and security of the dynamic track stabilizer.

scholarly journals A Frequency Domain Method for the Generation of Partially Coherent Normal Stationary Time Domain Signals

1993 ◽  
Vol 1 (1) ◽  
pp. 45-53 ◽  
Author(s):  
David O. Smallwood ◽  
Thomas L. Paez
Keyword(s):  
Density Matrix ◽  
Spectral Density ◽  
Frequency Domain ◽  
Time Domain ◽  
Frequency Domain Method ◽  
Complex Frequency ◽  
Arbitrary Length ◽  
Partially Coherent ◽  
Spectral Density Matrix ◽  
The Time Domain

A procedure for generating vectors of time domain signals that are partially coherent in a prescribed manner is described. The procedure starts with the spectral density matrix,[Gxx(f)], that relates pairs of elements of the vector random process{X(t)},−∞<t<∞. The spectral density matrix is decomposed into the form[Gxx(f)]=[U(f)][S(f)][U(f)]'where[U(f)]is a matrix of complex frequency response functions, and[S(f)]is a diagonal matrix of real functions that can vary with frequency. The factors of the spectral density matrix,[U(f)]and[S(f)], are then used to generate a frame of random data in the frequency domain. The data is transformed into the time domain using an inverse FFT to generate a frame of data in the time domain. Successive frames of data are then windowed, overlapped, and added to form a vector of normal stationary sampled time histories,{X(t)}, of arbitrary length.

Simple Method for Evaluation of Fatigue Damage of Structures in Wide-Band Random Vibrations

1994 ◽  
Vol 208 (1) ◽  
pp. 65-68 ◽  
Author(s):  
J J Kim ◽  
H Y Kim
Keyword(s):  
Spectral Density ◽  
Frequency Domain ◽  
Power Spectral Density ◽  
Fatigue Damage ◽  
Time Domain ◽  
Wide Band ◽  
Simple Method ◽  
Density Data ◽  
Power Spectral ◽  
The Time Domain

The note describes a simple method for evaluation of fatigue damage of structures in wide-band vibrations from response power spectral density data in the frequency domain. The method is applied to three sample cases and the results are compared with those of the damage calculation in the time domain.

Apodisation in the time domain

1992 ◽  
Vol 2 (4) ◽  
pp. 615-620
Author(s):  
G. W. Series
Keyword(s):  
Time Domain ◽  
The Time Domain
Sign in / Sign up

Export Citation Format

Share Document