Highly Configurable 100 Channel Recording and Stimulating Integrated Circuit for Biomedical Experiments

This paper presents the design results of a 100-channel integrated circuit dedicated to various biomedical experiments requiring both electrical stimulation and recording ability. The main design motivation was to develop an architecture that would comprise not only the recording and stimulation, but would also block allowing to meet different experimental requirements. Therefore, both the controllability and programmability were prime concerns, as well as the main chip parameters uniformity. The recording stage allows one to set their parameters independently from channel to channel, i.e., the frequency bandwidth can be controlled in the (0.3 Hz–1 kHz)–(20 Hz–3 kHz) (slow signal path) or (0.3 Hz–1 kHz)–4.7 kHz (fast signal path) range, while the voltage gain can be set individually either to 43.5 dB or 52 dB. Importantly, thanks to in-pixel circuitry, main system parameters may be controlled individually allowing to mitigate the circuitry components spread, i.e., lower corner frequency can be tuned in the 54 dB range with approximately 5% precision, and the upper corner frequency spread is only 4.2%, while the voltage gain spread is only 0.62%. The current stimulator may also be controlled in the broad range (69 dB) with its current setting precision being no worse than 2.6%. The recording channels’ input-referred noise is equal to 8.5 µVRMS in the 10 Hz–4.7 kHz bandwidth. The single-pixel occupies 0.16 mm2 and consumes 12 µW (recording part) and 22 µW (stimulation blocks).

Directional and frequency spread of surface ocean waves from CFOSAT/SWIM satelllite measurements

<p>The CFOSAT (China France Oceanography Satellite) mission launched in 2018 now routinely provides at the global scale, directional spectra of ocean waves. The principle is based on the analysis of the normalized radar cross-section measured by the instrument SWIM (Surface Waves Investigation and Monitoring), a near-nadir pointing Ku-Band real-aperture scanning radar. From the ocean wave spectra derived from SWIM, the principal parameters of ocean wave spectra as significant wave height, peak wavelength, and peak direction are now available to better characterize the sea-state. However, it is known that these principal parameters are not sufficient not fully characterize the distribution of wave energy and understand or validate the physical processes impacting its evolution during growth order decay. Here we show that the parameters characterizing the shape of the wave spectra (e.g directional and frequency spread) can be estimated at the global scale from the SWIM measurements. We also show that they can provide consistent values of the Benjamin-Feir index, an index proposed to estimate the probability of extreme waves. Similarities of differences with the shape parameters of the MFWAM numerical wave model are also discussed.</p>

An estimation of cost-based market liquidity from daily high, low and close prices

In the literature of asset pricing, this paper introduces a new method to estimate the cost-based market liquidity (CBML), that is, the bid-ask spread. The proposed model of spread proxy positively correlates with the examined low-frequency spread proxies for a larger dataset. The introduced approach provides potential implications in important aspects. Unlike in the Roll bid-ask spread model and the CHL bid-ask estimator, the CBML model consistently estimates market liquidity and trading cost for the entire dataset. Additionally, the CBML estimator steadily measures positive spreads, unlike in the CS bid-ask spread model. The construction of the proposed approach is not computationally intensive and can be considered for distinct studies at both market and firm levels.

Three Channel Wavelet Filter Banks With Minimal Time Frequency Spread for Classification of Seizure-Free and Seizure EEG Signals

The authors compute the classification accuracy of minimal time-frequency spread wavelet filter bank with three channels in discriminating seizure-free and seizure electroencephalogram (EEG) signals. Wavelet filter bank with three channels generates two wavelet functions and one scaling function at the first level of wavelet decomposition. A time-frequency localized filter bank can be generated by minimizing the time spread and frequency spread of any one or all the functions simultaneously. The minimal time-frequency spread wavelet filter bank with three channels of regularity order, one designed with several different time-frequency optimality criteria and length six, are chosen, and the effect of each optimality criterion on the discrimination of seizure-free and seizure EEG signals is computed. The classification accuracy for five different optimality criteria are computed. Time-frequency localized three-band filter bank of length six classifies, the seizure-free and seizure EEG signals of Bonn University EEG database, with 98.25% of accuracy.