A simple quadrature oscillator using only CCCDBAs and grounded capacitors

2007 ◽  
Author(s):  
Winai Jaikla ◽  
Phamorn Silapan ◽  
Montree Siripruchyanun
Keyword(s):  
Quadrature Oscillator ◽  
Simple Quadrature

A simple quadrature oscillator for generating triangular waves and square waves

1979 ◽  
Vol 67 (11) ◽  
pp. 1566-1567 ◽  
Author(s):  
B.Z. Kaplan ◽  
D. Har-Zahav ◽  
A. Blau
Keyword(s):  
Quadrature Oscillator ◽  
Simple Quadrature

Comments on "A simple quadrature oscillator for generating triangular waves and square waves"

1980 ◽  
Vol 68 (6) ◽  
pp. 744-744 ◽  
Author(s):  
J.R. Pimentel ◽  
B.Z. Kaplan ◽  
D. Har-Zahav ◽  
A. Blau
Keyword(s):  
Quadrature Oscillator ◽  
Simple Quadrature

scholarly journals Simple quadrature oscillator for BIST

2010 ◽  
Vol 46 (4) ◽  
pp. 271 ◽  
Author(s):  
J. Raman ◽  
P. Rombouts ◽  
L. Weyten
Keyword(s):  
Quadrature Oscillator ◽  
Simple Quadrature

Third order quadrature oscillator and its application using CDBA

2021 ◽  
Author(s):  
Mourina Ghosh ◽  
Shekhar Suman Borah ◽  
Ankur Singh ◽  
Ashish Ranjan
Keyword(s):  
Third Order ◽  
Quadrature Oscillator

scholarly journals Why simple quadrature is just as good as Monte Carlo

2020 ◽  
Vol 26 (1) ◽  
pp. 1-16
Author(s):  
Kevin Vanslette ◽  
Abdullatif Al Alsheikh ◽  
Kamal Youcef-Toumi
Keyword(s):  
Monte Carlo ◽  
Random Sampling ◽  
Bayesian Probability ◽  
Independent Factor ◽  
Worst Case ◽  
Statistical Equivalence ◽  
Deterministic Sampling ◽  
Quadrature Methods ◽  
Quadrature Sampling ◽  
Simple Quadrature

AbstractWe motive and calculate Newton–Cotes quadrature integration variance and compare it directly with Monte Carlo (MC) integration variance. We find an equivalence between deterministic quadrature sampling and random MC sampling by noting that MC random sampling is statistically indistinguishable from a method that uses deterministic sampling on a randomly shuffled (permuted) function. We use this statistical equivalence to regularize the form of permissible Bayesian quadrature integration priors such that they are guaranteed to be objectively comparable with MC. This leads to the proof that simple quadrature methods have expected variances that are less than or equal to their corresponding theoretical MC integration variances. Separately, using Bayesian probability theory, we find that the theoretical standard deviations of the unbiased errors of simple Newton–Cotes composite quadrature integrations improve over their worst case errors by an extra dimension independent factor {\propto N^{-\frac{1}{2}}}. This dimension independent factor is validated in our simulations.

scholarly journals Current-Mode Third-Order Quadrature Oscillator Using CDTAs

2009 ◽  
Vol 2009 ◽  
pp. 1-5 ◽  
Author(s):  
Jiun-Wei Horng
Keyword(s):  
Theoretical Analysis ◽  
Phase Difference ◽  
Oscillation Frequency ◽  
Current Mode ◽  
Third Order ◽  
Quadrature Oscillator ◽  
Oscillation Condition ◽  
Transconductance Amplifiers ◽  
Simulation Results ◽  
A Current

This paper describes a current-mode third-order quadrature oscillator based on current differencing transconductance amplifiers (CDTAs). Outputs of two current-mode sinusoids with90°phase difference are available in the quadrature oscillator circuit. The oscillation condition and oscillation frequency are orthogonal controllable. The proposed circuit employs only grounded capacitors and is ideal for integration. Simulation results are included to confirm the theoretical analysis.

DDCCTA-based quadrature oscillator

2013 ◽  
Author(s):  
Montree Kumngern ◽  
Anusorn Auttaput ◽  
Kobchai Dejhan
Keyword(s):  
Quadrature Oscillator
Sign in / Sign up

Export Citation Format

Share Document