Continuous weak measurement of a trapped electron using a percolation field effect transistor

We investigate the use of a percolation-field-effect-transistor for the continuous weak measurement of a spatially Rabi oscillating trapped electron through the change in percolation pathway of the transistor channel. In contrast to conventional devices, this detection mechanism in principle does not require a change in the stored energy of the gate capacitance to modify the drain current, so reducing the measurement back-action. The signal-to-noise ratio and measurement bandwidth are seen to be improved compared to conventional devices, allowing further aspects of the dynamic behaviour to be observed. © 2013 AIP Publishing LLC.

Capacity approaching codes for non-coherent orthogonal modulation

This paper describes a curve-fitting approach for the design of capacity approaching coded modulation for orthogonal signal sets with non-coherent detection. In particular, bit-interleaved coded modulation with iterative decoding is considered. Decoder metrics are developed that do not require knowledge of the signal-to-noise ratio, yet still offer very good performance. © 2007 IEEE.

A resonant micromachined electrostatic charge sensor

A micromachined electrometer, based on the concept of a variable capacitor, has been designed, modeled, fabricated, and tested. The device presented in this paper functions as a modulated variable capacitor, wherein a dc charge to be measured is up-modulated and converted to an ac voltage output, thus improving the signal-to-noise ratio. The device was fabricated in a commercial standard SOI micromachining process without the need for any additional processing steps. The electrometer was tested in both air and vacuum at room temperature. In air, it has a charge-to-voltage conversion gain of 2.06 nV/e, and a measured charge noise floor of 52.4 e/rtHz. To reduce the effects of input leakage current, an electrically isolated capacitor has been introduced between the variable capacitor and input to sensor electronics. Methods to improve the sensitivity and resolution are suggested while the long-term stability of these sensors is modeled and discussed. © 2006 IEEE.

A new, fast response CO2 sensor

The inability of emissions reduction methods to meet upcoming legislation without an unacceptable increase in vehicle cost is a major problem of automobile manufacturer. This work aims to develop a cost-effective reduction of automobile emissions. A prototype CO2 sensor with 5 msec response time was built and bench tested, then used on an engine. The sensor design was based on standard emissions measurement technology using non-dispersive IR absorption. An improved sensor has now been completed with significant improvements in terms of signal to noise ratio and long-term stability. The improved sensor will be used to measure CO2 concentrations on three different engines. The results will then be used to validate engine and catalyst models and to propose control strategies aimed at reducing overall emissions. A brief description of the sensor itself was presented. Original is an abstract.

Asymmetric quantizers are better at low SNR

We study the behavior of channel capacity when a one-bit quantizer is employed at the output of the discrete-time average-power-limited Gaussian channel. We focus on the low signal-to-noise ratio regime, where communication at very low spectral efficiencies takes place, as in Spread-Spectrum and Ultra-Wideband communications. It is well known that, in this regime, a symmetric one-bit quantizer reduces capacity by 2/π, which translates to a power loss of approximately two decibels. Here we show that if an asymmetric one-bit quantizer is employed, and if asymmetric signal constellations are used, then these two decibels can be recovered in full. © 2011 IEEE.

Nearest neighbour decoding and pilot-aided channel estimation in stationary Gaussian flat-fading channels

We study the information rates of non-coherent, stationary, Gaussian, multiple-input multiple-output (MIMO) flat-fading channels that are achievable with nearest neighbour decoding and pilot-aided channel estimation. In particular, we analyse the behaviour of these achievable rates in the limit as the signal-to-noise ratio (SNR) tends to infinity. We demonstrate that nearest neighbour decoding and pilot-aided channel estimation achieves the capacity pre-logwhich is defined as the limiting ratio of the capacity to the logarithm of SNR as the SNR tends to infinityof non-coherent multiple-input single-output (MISO) flat-fading channels, and it achieves the best so far known lower bound on the capacity pre-log of non-coherent MIMO flat-fading channels. © 2011 IEEE.

Gaussian fading is the worst fading

The capacity of peak-power limited, single-antenna, noncoherent, flat-fading channels with memory is considered. The emphasis is on the capacity pre-log, i.e., on the limiting ratio of channel capacity to the logarithm of the signal-to-noise ratio (SNR), as the SNR tends to infinity. It is shown that, among all stationary and ergodic fading processes of a given spectral distribution function and whose law has no mass point at zero, the Gaussian process gives rise to the smallest pre-log. The assumption that the law of the fading process has no mass point at zero is essential in the sense that there exist stationary and ergodic fading processes whose law has a mass point at zero and that give rise to a smaller pre-log than the Gaussian process of equal spectral distribution function. An extension of these results to multiple-input single-output (MISO) fading channels with memory is also presented. © 2006 IEEE.

Gaussian fading is the worst fading

The capacity of peak-power limited, single-antenna, non-coherent, flat-fading channels with memory is considered. The emphasis is on the capacity pre-log, i.e., on the limiting ratio of channel capacity to the logarithm of the signal-to-noise ratio (SNR), as the SNR tends to infinity. It is shown that, among all stationary & ergodic fading processes of a given spectral distribution function whose law has no mass point at zero, the Gaussian process gives rise to the smallest pre-log. © 2006 IEEE.

Deconvolution and elastography based on dimensional ultrasound

This paper is in two parts and addresses two of getting more information out of the RF signal from three-dimensional (3D) mechanically-swept medical ultrasound . The first topic is the use of non-blind deconvolution improve the clarity of the data, particularly in the direction to the individual B-scans. The second topic is imaging. We present a robust and efficient approach to estimation and display of axial strain information. deconvolution, we calculate an estimate of the point-spread at each depth in the image using Field II. This is used as of an Expectation Maximisation (EM) framework in which ultrasound scatterer field is modelled as the product of (a) a smooth function and (b) a fine-grain varying function. the E step, a Wiener filter is used to estimate the scatterer based on an assumed piecewise smooth component. In the M , wavelet de-noising is used to estimate the piecewise smooth from the scatterer field. strain imaging, we use a quasi-static approach with efficient based algorithms. Our contributions lie in robust and 3D displacement tracking, point-wise quality-weighted , and a stable display that shows not only strain but an indication of the quality of the data at each point in the . This enables clinicians to see where the strain estimate is and where it is mostly noise. deconvolution, we present in-vivo images and simulations quantitative performance measures. With the blurred 3D taken as OdB, we get an improvement in signal to noise ratio 4.6dB with a Wiener filter alone, 4.36dB with the ForWaRD and S.18dB with our EM algorithm. For strain imaging show images based on 2D and 3D data and describe how full D analysis can be performed in about 20 seconds on a typical . We will also present initial results of our clinical study to explore the applications of our system in our local hospital. © 2008 IEEE.