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Level Control and Special Circuits
Published in Douglas Self, Small Signal Audio Design, 2020
Most noise generators these days are digital, using calculations to produce pseudo-random white noise that is tightly defined in amplitude and spectral content. There are several ways to generate pseudo-random noise, of which the most common is the use of maximal-length sequences. These sequences repeat eventually and need to be rather longer than you might think to avoid any audible patterns in the noise; 10 seconds is a good starting value. There are other ways to produce pseudo-random noise, such as Kasami codes, but that is rather outside the province of this analogue book, so instead we will take a quick look at analogue noise generation.
A modified bidirectional long short-term memory neural network for rail vehicle suspension fault detection
Published in Vehicle System Dynamics, 2022
Yuejian Chen, Gang Niu, Yifan Li, Yongbo Li
We considered seven health states: healthy; stiffness of secondary suspension Ksz1 being reduced by 10% to its nominal value due to any fault like wear or material deterioration, by 20%, and by 30%; damping of secondary suspension Csz1 being reduced by 10% to its nominal value, by 20%, and by 30%. These are the same fault conditions Aravanis et al. [19] considered. Under each health state, 200 segments were simulated as testing data. As for training and validation, 50 segments were simulated under the healthy state. Each data segment was simulated using a different seed number of the random Gaussian white noise generator. Table 2 summarises the number of segments we simulated for model training, validation, and testing purposes.
Implementation and evaluation of ASHRAE’s acoustic Performance Measurement Protocols
Published in Science and Technology for the Built Environment, 2019
Gabrielle McMorrow, Liping Wang
There are two methods to measure reverberation time in a room: the impulse excitation method and the interrupted noise method. Each method will allow you to calculate the reverberation time, or time it takes for a sound to drop 60 dB in a room. What differs is your measurement setup and noise generator. In the impulse excitation method, the popping of a balloon was used as the noise. Reverberation time was measured using the “Reverberation Time” template installed on the sound-level meter. Measurements were performed according to the impulse excitation method, using the popping of a balloon as the impulse. The sound-level meter recorded the reverberation time measurements for each ⅓-octave band between frequencies of 250 Hz to 4,000 Hz. In rooms where more than one measurement was taken, an arithmetic average of decay at each frequency was calculated and is presented. Differences in reverberation times at different locations within the room can be significant. Building One’s Office 32A measurement locations and results are summarized in Figure 15 and Table 4. The maximum reverberation time from 250–4000 Hz is 0.64 s. This value does not comply with the recommended sound criteria for private offices within office buildings, which is less than 0.6 s.
Design and Development of FPGA-Based Spectrum Analyzer
Published in IETE Journal of Education, 2018
Rupali Borade, Akash Dimber, Damayanti Gharpure, Subramaniam Ananthakrishnan
The FFT-based spectrum analyzer implemented on the FPGA platform is designed for the proposed space payload to study low-frequency radio astronomical observation. The FPGA-based spectrum analyzer can easily be used for many other real-world applications and for education purpose as well. It was successfully used for antenna characterization and radio noise measurements. Moreover, these measurements were also carried out at remote places by making the FPGA-based spectrum analyzer standalone. It has also been used to test the performance of various electronics devices such as LNA, filters, noise generator, etc. It is also applicable for ADC characterization where output samples from an ADC are processed with an FFT to measure the integral nonlinearity, distortion, and signal-to-noise ratio. For education purpose, the FPGA-based spectrum analyzer provides a low-cost platform to understand frequency-domain behaviour of various signals as well as to study different signal processing concepts.