Effect of reduced temperature on the fT ofAlGaAs/GaAs heterojunction bipolar transistors

The high-frequency and DC performances of single-heterojunction Al _0.25Ga_0.75As/GaAs heterojunction bipolar transistors (HBTs) have been measured at temperatures between 300 and 110 K. It is found that the maximum unity-current-gain cutoff frequency increases from 26 GHz at 300 K to 34 GHz at 110 K. It is shown that electron diffusion as determined from the majority-carrier mobility does not accurately estimate the base transit time, at least until corrections for degeneracy and minority-carrier mobility enhancement are included. Reasonable agreement is obtained assuming that base transport is limited by the thermal velocity of electrons at reduced temperatures     

A 580-μW 1.8–6 GHz Multiband Switched-Resonator SiGe VCO With 0.3-V Supply Voltage

This letter presents a fully integrated low-power low-voltage multiband switched-resonator differential cross-coupled voltage controlled oscillator (VCO) implemented in 0.18 SiGe-BiCMOS technology. The VCO operates with a supply voltage as low as 0.29 V, owing to the low knee-voltage provided by the technology, and consumes a total power of 580 muW. Utilizing a switched-resonator, the VCO covers a wide switched frequency range of 1.83-2.97 GHz and 4.36-6.17 GHz with measured phase noise of around 112.2 dBc/Hz with 0.29 V supply and 119.7 dBc/Hz with 1 V supply at 1 MHz offset. Since high-frequency bands experience higher phase noise than the low frequency bands, high- short microstrip line inductors have been used for the high-frequency bands. To the best of the authors' knowledge, the reported VCO achieves the widest switched frequency tuning range with lowest core supply voltage.     

Fine-tuning commercial and military radio design

Software-defined radio (SDR) and cognitive radio (CR) concepts have been introduced to change the paradigm of wireless communications by making it possible to improve data throughput and connectivity by enabling autonomous reconfigurability spectral and temporal agility, and adaptive behavior. This new class of intelligent radio would be able to adapt to a wide variety of wireless operating conditions and multiple protocol standards, which will allow collaboration between otherwise incompatible systems.     

In(Ga)As/GaAs self-organized quantum dot lasers: DC andsmall-signal modulation properties

Self-organized growth of InGaAs/GaAs strained epitaxial layers gives rise to an ordered array of islands via the Stranski-Krastanow growth mode, for misfits >1.8%. These islands are pyramidal in shape with a base diagonal of ~20 nm and height of ~6-7 nm, depending of growth parameters. They therefore exhibit electronic properties of zero-dimensional systems, or quantum dots. One or more layers of such quantum dots can be stacked and vertically coupled to form the gain region of lasers. We have investigated the properties of such single-layer quantum dot (SLQD) and multilayer quantum dot (MLQD) lasers with a variety of measurements, including some at cryogenic temperatures. The experiments have been complemented with theoretical calculations of the electronic properties and carrier scattering phenomena in the dots. Our objective has been to elucidate the intrinsic behavior of these devices. The lasers exhibit temperature independent threshold currents up to 85 K, with T₀⩽670 K. Typical threshold currents of 200-μm long room temperature lasers vary from 6 to 20 mA. The small-signal modulation bandwidths of ridge waveguide lasers are 5-7.5 GHz at 300 K and increased to >20 GHz at 80 K. These bandwidths agree well with electron capture times of ~30 ps determined from high-frequency laser impedance measurements at 300 K and relaxation times of ~8 ps measured at 18 K by differential transmission pump-probe experiments. From the calculated results we believe that electron-hole scattering intrinsically limits the high-speed performance of these devices, in spite of differential gains as high as ~7×10^-14 cm² at room temperature     

An automatic channel selection method based on the standard deviation of wavelet coefficients for motor imagery based brain–computer interfacing

The redundant data in multichannel electroencephalogram (EEG) signals significantly reduces the performance of brain–computer interface (BCI) systems. By removing redundant channels, a channel selection strategy increases the classification accuracy of BCI systems. In this work, a novel channel selection method (stdWC) based on the standard deviation of wavelet coefficients across channels is proposed to identify Motor Imagery (MI) based EEG signals. The wavelet coefficients are calculated by employing a Continuous Wavelet Transform (CWT) filter bank to decompose each trial from the EEG channel. The wavelet coefficient's standard deviation values are obtained across the channels, and these values are then sorted to determine the EEG channels with the highest standard deviation values. The channels with the largest wavelet coefficient divergence are chosen. MI trials are then spatially filtered with the Common Spatial Pattern (CSP), and CWT filter bank-based 2D images are generated from the spatially filtered trials. These images are then classified using a unique nine-layered convolutional neural network (CNN) model that combines two feature maps acquired with differing filter sizes. The proposed framework (stdWC-CSP-CNN) is evaluated using kappa score and classification accuracy on two publically accessible datasets (BCI Competition III dataset IVa and BCI Competition IV dataset 2a). The suggested framework achieved a mean test classification accuracy of 88.8% for dataset IVa from BCI Competition III and 75.03% for dataset 2a from BCI Competition IV, according to the results. The proposed channel selection method outperforms the other channel selection methods examined, according to the results. By rejecting redundant channels, the whole framework can improve the performance of MI-based BCIs.     

Detection,tracking, and recognition of isolated multi-stroke gesticulated characters

Pattern Analysis and Applications - The detection and tracking of the bare hand are the most vital stages in the bare hand gesticulated character recognition system. Applying detection and tracking...