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High-frequency measurements noise

The presentation of the result in the frequency domain offers an additional advantage. The reactor behaviour modelled (Comb. Chamber (,i) can be directly compared with the behaviour calculated (Comb. Chamberc t,). The calculated frequency response of the reactor is the ratio of Che measured output and input spectra. This comparison is not possible in the time domain due to the measurement noise at high frequencies. This noise is amplified by the compensation of the measurement dynamics and thus no useful presentation of data is possible in the time domain. [Pg.580]

Smith, D.C. 1993. High Frequency Measurement and Noise in Electronic Circuits. Van Nostrand Reinhold, New York. [Pg.40]

Figure 10.16 Ideal noise spectral density versus frequency. Note the increase at low frequencies, the flat region ( white noise ), and the eventual falloff at very high frequencies. Measured data will not be as smooth, and will have spikes at some frequencies due to external source (60 Hz power, fluorescent lights, etc.). Figure 10.16 Ideal noise spectral density versus frequency. Note the increase at low frequencies, the flat region ( white noise ), and the eventual falloff at very high frequencies. Measured data will not be as smooth, and will have spikes at some frequencies due to external source (60 Hz power, fluorescent lights, etc.).
A novel optimization approach based on the Newton-Kantorovich iterative scheme applied to the Riccati equation describing the reflection from the inhomogeneous half-space was proposed recently [7]. The method works well with complicated highly contrasted dielectric profiles and retains stability with respect to the noise in the input data. However, this algorithm like others needs the measurement data to be given in a broad frequency band. In this work, the method is improved to be valid for the input data obtained in an essentially restricted frequency band, i.e. when both low and high frequency data are not available. This... [Pg.127]

The ultrasonic images that we want to process are HF- type, (i.e., huilt from High Frequency signals. Fig. 4). Consequently, the noise is situated in the eentral part of the matrix. In order that we define two thresholds tl and t2. These last will be determined by using one of some measures quoted in the bibliography. [Pg.235]

The main error sources are noise in the wavefront sensor measurement, imperfect wavefront correction due to the finite number of actuators and bandwidth error due to the finite time required to measure and correct the wavefront error. Other errors include errors in the telescope optics which are not corrected by the AO system (e.g. high frequency vibrations, high spatial frequency errors), scintillation and non-common path errors. The latter are wavefront errors introduced in the corrected beam after light has been extracted to the wavefront sensor. Since the wavefront sensor does not sense these errors they will not be corrected. Since the non-common path errors are usually static, they can be measured off-line and taken into account in the wavefront correction. [Pg.195]

Because the noise usually contaminates the high frequencies, smoothness is a very common regularization constraint. Smoothness can be enforced if 0prior(x) is some measure of the roughness of the sought distribution x, for instance (in 1-D) ... [Pg.411]

About measurements in the presence of a high-frequency noise... [Pg.208]

Apparatus. All electrical resistances were measured with an electrolytic conductivity bridge (Leeds and Northrup model 4666) which was constructed according to specifications set forth by Jones (28) and described by Dike (29). The audio-frequency source was a General Radio Co. type 1311-A audio oscillator used with the frequency regulated at 1000 Hz and the output at about 5 V. The detector circuit consisted of a high-gain low-noise tuned amplifier and null detector (General Radio Co. type 1232-A) and an oscilloscope (Heathkit model O-ll) ... [Pg.251]


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