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A low-power low-noise logarithmic preamplifier for biopotential and neural recording application is presented. The logarithmic amplifier based on a True Logarithmic Amplifier technique which has been simulated in a UMC standard 90-nm 1P9M CMOS process consumes 11μW from a 1.2V power supply. The simulated input referred noise is 6.7μV over 0.1 Hz to 20 kHz.
There have been significant advances in fabrication of high-density microelectrode arrays using silicon micromachining technology in neural signal recording systems. The interface between microelectrodes and chemical environment brings great interest to researchers working on extracellular stimulation. This interface is quite complex and must be modeled carefully to match experimental results. Computer...
A fully differential, low-power, area-efficient analog to digital converter has been designed and simulated for implantable neural signal recording systems. Proposed ADC consisted of an analog stage, similar to a pipeline converter stages but reused it to extract the final effective bits. This paper presents a 9-bit 1-MSample/s analog to digital converter with stage reused technique that has been...
A fully-differential low-power low-noise preamplifier for biopotential and neural-recording applications is presented. This design, which has been simulated in a standard 90-nm CMOS process, consumes 30 μW from a 3-V power supply. The simulated integrated input-referred noise is 2.3 μV over 0.1 Hz to 20 kHz. The amplifier also provides an output swing of ± 0.9 V with a THD of less than 0.1%
Widely used demodulation technique in EIT/EIS systems is the direct conversion (zero-IF) method in which measured single tone current (or voltage) signal is mixed with source waveform at the same frequency, so that the magnitude and phase of the measured current (or voltage) can be determined after a low pass filtering stage. This is especially true for an EIS system which might need to operate in...
There is an increasing trend in several biomedical applications such as ECG, PCG, EEG, neural recording, temperature sensing, and blood pressure for signals to be sensed in small portable wireless devices. In this way, analog to digital converters play the main role in these systems. This paper proposes a 10-bit 50-MSample/s pipeline analog to digital converter that has been designed and simulated...
An artificial neural network (ANN) was implemented on an FPGA to predict cetane number in diesel fuel from its chemical compositions, extracted by liquid chromatography (LC) and gas chromatography (GC). An MLP network is used. To train the MLP, two variants of the backpropagation algorithm are utilized: backpropagation with plummeting learning rate factor and backpropagation with declining learning-rate...
This paper presents a low noise amplifier (LNA) with an input impedance matching technique using mutual coupled stack inductors. Two different input matching methodologies using mutual inductors are evaluated in terms of their effect on the gain and NF of RF CMOS LNAs in 2.4 GHz. Design guidelines to improve the gain-NF performance of CMOS LNAs are developed by means of analytical expressions. Moreover,...
Dynamic reconfiguration has always constituted a challenge for embedded systems designers. Nowadays, technological developments make possible to do it on Xilinx FPGAs, but setting up a dynamically reconfigurable system remains a painful and complicated task. This architecture can benefit from being able to load and unload modules at run-time and using this feature, significant reduction in hardware...
A monolithic CMOS microsystem for nuclear magnetic resonance applications has been designed and tested. It includes two planar microcoils and a complete readout electronics with a single 3.3 V supply. It measures static fields around 1 T with a field resolution better than 1 ppm/√Hz. The probe can also be used for NMR spectroscopy with a spectral resolution of 15 Hz. The resolution is mainly limited...
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