Implantable Microsystem for Wireless Neural Recording Applications

A prototype microsystem is presented for wireless neural recording application. An inductive link was built for transcutaneous wireless power transfer and data transmission. Total 16.5 mW power and 50 bps - 2.5 Kbps command data can be received over 1 - 5 MHz with a distance of 0-10 mm. The integrated amplifiers were designed with a limited bandwidth for neural signals acquisition. The gain of 60 dB was obtained by preamplifier at 7 Hz - 3 KHz. An integrated FM transmitter was used to transmit the extracted neural signals to external equipments with 0.374 - 2 mW power comsumption and a maximum data rate of 500 Kbps at 100 MHz. All the integrated circuits modules except the power recovery circuit were tested or stimulated under a 3.3 V power supply, and fabricated in standard CMOS processing.

SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79 . 1.45 . 1.18-competitive separately for traditional timeout PM . adaptive predictive PM and stochastic PM.

Recent research results on deep level defects in semi-insulating InP - Application to improve material quality

An apparent defect suppression effect has been observed in InP through an investigation of deep level defects in different semi-insulating (SI) InP materials. Quality improvement of SI-InP based on the defect suppression mechanism is presented.

Micro-raman investigation of defects in a 4H-SiC homoepilayer

Three types of defects, namely defect I, defect 11, defect 111, in the 4H-SiC homoepilayer were investigated by micro-raman scattering measurement. These defects all originate from a certain core and are composed of (1) a wavy tail region, (11) two long tails, the so called comet and (111) three plaits. It was found that there are 3C-SiC inclusions in the cores of defect 11 and defect III and the shape of inclusion determines the type of defect II or defect III. If the core contains a triangle-shaped inclusion, the defect III would be formed; otherwise, the defect 11 was formed. No inclusion was observed in the core of the defect I. The mechanisms of these defects are discussed.

A DSWN-based specific-purpose neural computing system

The Double Synapse Weighted Neuron (DSWN) is a kind of general-purpose neuron model, which with the ability of configuring Hyper-sausage neuron (HSN). After introducing the design method of hardware DSWN synapse, this paper proposed a DSWN-based specific purpose neural computing device-CASSANN-IIspr. As its application, a rigid body recognition system was developed on CASSANN-IIspr, which achieved better performance than RIBF-SVMs system.

Hypersausage neural networks and its application in face recognition

In this paper, we firstly give the nature of 'hypersausages', study its structure and training of the network, then discuss the nature of it by way of experimenting with ORL face database, and finally, verify its unsurpassable advantages compared with other means.

Morphological defects and uniformity issues of 4H-SiC homoepitaxial layers grown on off-oriented (0001)Si faces

The morphological defects and uniformity of 4H-SiC epilayers grown by hot wall CVD at 1500 degrees C on off-oriented (0001) Si faces are characterized by atomic force microscope, Nomarski optical microscopy, and Micro-Raman spectroscopy. Typical morphological defects including triangular defects, wavy steps, round pits, and groove defects are observed in mirror-like SiC epilayers. The preparation of the substrate surface is necessary for the growth of high-quality 4H-SiC epitaxial layers with low-surface defect density under optimized growth conditions. (c) 2006 Elsevier Ltd. All rights reserved.

Electron irradiation-induced defects in InP pre-annealed at high temperature

Electron irradiation-induced deep level defects have been studied in InP which has undergone high-temperature annealing in phosphorus and iron phosphide ambients, respectively. In contrast to a high concentration of irradiation-induced defects in as-grown and phosphorus ambient annealed InP, InP pre-annealed in iron phosphide ambient has a very low concentration of defects. The phenomenon has been explained in terms of a faster recombination of radiation-induced defects in the annealed InP. The radiation-induced defects in the annealed InP have been compared and studied. (c) 2006 Elsevier Ltd. All rights reserved.

Growth of high quality semi-insulating InP single crystal by suppression of compensation defects

Deep level defects in as-grown and annealed SI-InP samples were investigated by thermally stimulated current spectroscopy. Correlations between electrical property, compensation ratio, thermal stability and deep defect concentration in SI-InP were revealed. An optimized crystal growth condition for high quality SI-InP was demonstrated based on the experimental results.

Circuit design and simulation of a CMOS-based preamplifier for brain neural signals

A novel CMOS-based preamplifier for amplifying brain neural signal obtained by scalp electrodes in brain-computer interface (BCI) is presented in this paper. By means of constructing effective equivalent input circuit structure of the preamplifier, two capacitors of 5 pF are included to realize the DC suppression compared to conventional preamplifiers. Then this preamplifier is designed and simulated using the standard 0.6 mu m MOS process technology model parameters with a supply voltage of 5 volts. With differential input structures adopted, simulation results of the preamplifier show that the input impedance amounts to more than 2 Gohm with brain neural signal frequency of 0.5 Hz-100 Hz. The equivalent input noise voltage is 18 nV/Hz(1/2). The common mode rejection ratio (CMRR) of 112 dB and the open-loop differential gain of 90 dB are achieved.

Improvement of the electrical property of semi-insulating InP by suppression of compensation defects

Semi-insulating (SI) InP obtained by iron phosphide ambient annealing has very low concentration of deep level defects and better electrical property than SI-InP annealed in phosphorus ambient. The defect suppression phenomenon correlates with Fe diffusion and substitution in the annealing process. Analysis of the experimental result suggests that a high activation ratio of incorporated Fe in InP has an effect of defect suppression in Fe-doped and Fe-diffused SI-InP.

STUDY OF MICROSTRUCTURE AND DEFECTS IN HYDROGENATED MICROCRYSTALLINE SILICON FILMS

Microcrystalline silicon films were deposited by very high frequency (VHF) plasma-enhanced chemical vapor deposition (PECVD) with different hydrogen dilution. The microstructure of these films was investigated using Raman spectroscopy and infrared absorption (IR) spectra. The crystalline, amorphous, and grain boundary volume fractions X-c, X-a and X-gb were estimated from Raman measurements. An interface structure factor (R-if) is proposed to characterize the grain boundary volume fractions in IR spectroscopy. The density of states (DOS) of the microcrystalline crystalline silicon films were studied by phase-shift analysis of modulated photocurrent (MPC) and photoconductivity spectroscopy. It was observed that DOS increases with increasing grain boundary volume fractions, while the values of electron mobility-lifetime product mu T-e(e) disease.

on string languages generated by spiking neural p systems

We continue the study of spiking neural P systems by considering these computing devices as binary string generators: the set of spike trains of halting computations of a given system constitutes the language generated by that system. Although the "direct" generative capacity of spiking neural P systems is rather restricted (some very simple languages cannot be generated in this framework), regular languages are inverse-morphic images of languages of finite spiking neural P systems, and recursively enumerable languages are projections of inverse-morphic images of languages generated by spiking neural P systems.