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Bulk Acoustic Wave Gyroscopes
Published in Vikas Choudhary, Krzysztof Iniewski, MEMS, 2017
Dynamic range, another important performance parameter in gyroscopes, refers to the range of input rates over which the output is detectable. It is typically computed as the ratio between the maximum input rotation rate (full-scale rate) that the sensor can tolerate and the system noise floor. To ensure linear operation, the maximum input rate is considered to be reached when the disk deforms one-tenth of the capacitive gap. Also, it is assumed that the electronic noise can be reduced substantially employing advanced low-noise front-end circuitry, leaving Brownian noise as the dominant noise source. To estimate the dynamic range, the maximum input rotation rate is divided by the product of the Brownian noise and the square root of the device bandwidth. The bandwidth of the device is replaced by (fresonance/2Qmode-matched) and the dynamic range for these devices is stated as Dynamic Range=q2−maxω01.5M4kBTQBW=0.1d0ω04πM4kBT
The Basics
Published in Douglas Self, Small Signal Audio Design, 2020
Red noise has energy per Hz falling at 6 dB per octave rather than 3. It is important in the study of stochastic processes and climate models but has little application in audio. The only place you are likely to encounter it is in the oscillator section of analogue synthesisers. It is sometimes called Brownian noise, as it can be produced by Brownian motion; hence its alternative name of random-walk noise. Brown here is a person and not a colour. [21]
Basics
Published in Douglas Self, Small Signal Audio Design, 2014
Red noise has energy per Hz falling at 6 dB per octave rather than 3. It is important in the study of stochastic processes and climate models, but has little application in audio. The only place you are likely to encounter it is in the oscillator section of analogue synthesisers. It is sometimes called Brownian noise as it can be produced by Brownian motion, hence its alternative name of random-walk noise. Brown here is a person and not a colour [6].
Skill level changes the coordination and variability of standing posture and movement in a pistol-aiming task
Published in Journal of Sports Sciences, 2018
Ji-Hyun Ko, Dong-Wook Han, Karl M Newell
The detrended fluctuation analysis (DFA) was also conducted to estimate the complexity of the pistol and COP motions. DFA has been used to measure the fractal dimension of a time series because of its reduced dependence on a non-stationary noise–like data where the statistical properties constantly change over time (Costa et al., 2002). To estimate the DFA exponent () that is an index of the complexity, first the root mean square of the detrended residuals, , was calculated in non–overlapping time scales (ts). Then, the DFA () was numerically defined as the linear slope of log10[] against to log10[ts] which was calculated by a linear regression. If the DFA () is 1.5 the complexity of time series is consistent with Brownian noise, while if it is close to 0.5 the complexity is similar to White noise.