Continous Time Sigma-Delta Modulator Employing a Novel Comparator Architecture

A novel comparator architecture is proposed for speed operation in low voltage environment. Performance comparison with a conventional regenerative comparator shows a speed-up of 41%. The proposed comparator is embedded in a continuous time sigma-delta ADC so as to reduce the quantizer delay and hence minimizes the excess loop delay problem. A performance enhancement of 1dB in the dynamic range of the ADC is achieved with this new comparator. We have implemented this ADC in a standard single-poly 8-Metal 0.13 mum UMC process. The entire system operates at 1.2 V supply providing a dynamic range of 32 dB consuming 720 muW of power and occupies an area of 0.1 mm2.

Estimation of missing data using windowed linear prediction in laterally truncated projection & in cone beam CT

In this paper, we address the reconstruction problem from laterally truncated helical cone-beam projections. The reconstruction problem from lateral truncation, though similar to that of interior radon problem, is slightly different from it as well as the local (lambda) tomography and pseudo-local tomography in the sense that we aim to reconstruct the entire object being scanned from a region-of-interest (ROI) scan data. The method proposed in this paper is a projection data completion approach followed by the use of any standard accurate FBP type reconstruction algorithm. In particular, we explore a windowed linear prediction (WLP) approach for data completion and compare the quality of reconstruction with the linear prediction (LP) technique proposed earlier.

MAX: A Multi Objective Memory Architecture eXploration Framework for Embedded Systems-on-Chip

Today's feature-rich multimedia products require embedded system solution with complex System-on-Chip (SoC) to meet market expectations of high performance at a low cost and lower energy consumption. The memory architecture of the embedded system strongly influences these parameters. Hence the embedded system designer performs a complete memory architecture exploration. This problem is a multi-objective optimization problem and can be tackled as a two-level optimization problem. The outer level explores various memory architecture while the inner level explores placement of data sections (data layout problem) to minimize memory stalls. Further, the designer would be interested in multiple optimal design points to address various market segments. However, tight time-to-market constraints enforces short design cycle time. In this paper we address the multi-level multi-objective memory architecture exploration problem through a combination of Multi-objective Genetic Algorithm (Memory Architecture exploration) and an efficient heuristic data placement algorithm. At the outer level the memory architecture exploration is done by picking memory modules directly from a ASIC memory Library. This helps in performing the memory architecture exploration in a integrated framework, where the memory allocation, memory exploration and data layout works in a tightly coupled way to yield optimal design points with respect to area, power and performance. We experimented our approach for 3 embedded applications and our approach explores several thousand memory architecture for each application, yielding a few hundred optimal design points in a few hours of computation time on a standard desktop.

AC Breakdown Characteristics of Epoxy Nanocomposites

Experiments were conducted to measure the ac breakdown strength of epoxy alumina nanocomposites with different filler loadings of 0.1, 1 and 5 wt%. The experiments were performed as per the ASTM D 149 standard on samples of thickness 0.5 mm, 1 mm and 3 mm in order to study the effect of thickness on the ac breakdown strength of epoxy nanocomposites. In the case of epoxy alumina nanocomposites it was observed that the ac breakdown strength was marginally lower for 0.1 wt% and 1 wt% filler loadings and then increased at 5 wt% filler loading as compared to the unfilled epoxy. The Weibull shape parameter (beta) increased with the addition of nanoparticles to epoxy as well as with the increasing sample thickness for all the filler loadings considered. DSC analysis was done to study the material properties at the filler resin interface in order to understand the effect of the filler loading and thereby the influence of the interface on the ac breakdown strength of epoxy nanocomposites. It was also observed that the decrease in ac electric breakdown strength with an increase in sample thickness follows an inverse power-law dependence. In addition, the ac breakdown strength of epoxy silica nanocomposites have also been studied in order to understand the influence of the filler type on the breakdown strength.

VLSI Implementation of Spatial prediction Based Image Compression Scheme

We propose the design and implementation of hardware architecture for spatial prediction based image compression scheme, which consists of prediction phase and quantization phase. In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates an error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. The software model is tested for its performance in terms of entropy, standard deviation. The memory and silicon area constraints play a vital role in the realization of the hardware for hand-held devices. The hardware architecture is constructed for the proposed scheme, which involves the aspects of parallelism in instructions and data. The processor consists of pipelined functional units to obtain the maximum throughput and higher speed of operation. The hardware model is analyzed for performance in terms throughput, speed and power. The results of hardware model indicate that the proposed architecture is suitable for power constrained implementations with higher data rate

The Case for Non-Cooperative Multihoming of Users to Access Points in IEEE 802.11 WLANs

In many cases, a mobile user has the option of connecting to one of several IEEE 802.11 access points (APs),each using an independent channel. User throughput in each AP is determined by the number of other users as well as the frame size and physical rate being used. We consider the scenario where users could multihome, i.e., split their traffic amongst all the available APs, based on the throughput they obtain and the price charged. Thus, they are involved in a non-cooperative game with each other. We convert the problem into a fluid model and show that under a pricing scheme, which we call the cost price mechanism, the total system throughput is maximized,i.e., the system suffers no loss of efficiency due to selfish dynamics. We also study the case where the Internet Service Provider (ISP) could charge prices greater than that of the cost price mechanism. We show that even in this case multihoming outperforms unihoming, both in terms of throughput as well as profit to the ISP.

An analytical model for an IEEE~802.11 WLAN using DCF with two types of VoIP calls

In this paper we develop and numerically explore the modeling heuristic of using saturation attempt probabilities as state dependent attempt probabilities in an IEEE 802.11e infrastructure network carrying packet telephone calls and TCP controlled file downloads, using enhanced distributed channel access (EDCA). We build upon the fixed point analysis and performance insights. When there are a certain number of nodes of each class contending for the channel (i.e., have nonempty queues), then their attempt probabilities are taken to be those obtained from saturation analysis for that number of nodes. Then we model the system queue dynamics at the network nodes. With the proposed heuristic, the system evolution at channel slot boundaries becomes a Markov renewal process, and regenerative analysis yields the desired performance measures. The results obtained from this approach match well with ns2 simulations. We find that, with the default IEEE 802.11e EDCA parameters for AC 1 and AC 3, the voice call capacity decreases if even one file download is initiated by some station. Subsequently, reducing the voice calls increases the file download capacity almost linearly (by 1/3 Mbps per voice call for the 11 Mbps PHY)

Design and Optimization of Broadband Micromachined Antenna

Performance improvement of a micromachined patch antenna operating at 30 GHz with a capacitively coupled feed arrangement is presented here. Such antennas are useful for monolithic integration with active components. Specifically, micromachining can be employed to achieve a low dielectric constant region under the patch which causes (i) the suppression of surface waves and hence the increase in radiation efficiency and (ii) increase in the bandwidth. The performance of such a patch antenna can be significantly improved by selecting a coupled feed arrangement. We have optimized the dimensions and location of the capacitive feeding strip to get the maximum improvement in bandwidth. Since this is a totally planar arrangement, and does not involve any stacked structures, this antenna is easy to fabricate using standard microfabrication techniques. The antenna element thus designed has a -10 dB bandwidth of 1600 MHz

Distributed load adaptive scheduling for throughput and delay guarantees in fading wireless LANs

We consider a problem of providing mean delay and average throughput guarantees in random access fading wireless channels using CSMA/CA algorithm. This problem becomes much more challenging when the scheduling is distributed as is the case in a typical local area wireless network. We model the CSMA network using a novel queueing network based approach. The optimal throughput per device and throughput optimal policy in an M device network is obtained. We provide a simple contention control algorithm that adapts the attempt probability based on the network load and obtain bounds for the packet transmission delay. The information we make use of is the number of devices in the network and the queue length (delayed) at each device. The proposed algorithms stay within the requirements of the IEEE 802.11 standard.

Perceptually motivated Rated Controller for Video coding

Rate control regulates the instantaneous video bit -rate to maximize a picture quality metric while satisfying channel constraints. Typically, a quality metric such as Peak Signalto-Noise ratio (PSNR) or weighted signal -to-noise ratio(WSNR) is chosen out of convenience. However this metric is not always truly representative of perceptual video quality.Attempts to use perceptual metrics in rate control have been limited by the accuracy of the video quality metrics chosen.Recently, new and improved metrics of subjective quality such as the Video quality experts group's (VQEG) NTIA1 General Video Quality Model (VQM) have been proven to have strong correlation with subjective quality. Here, we apply the key principles of the NTIA -VQM model to rate control in order to maximize perceptual video quality. Our experiments demonstrate that applying NTIA -VQM motivated metrics to standard TMN8 rate control in an H.263 encoder results in perceivable quality improvements over a baseline TMN8 / MSE based implementation.

A New Iterative FIR Filter for Image and Video Restoration

Image and video filtering is a key image-processing task in computer vision especially in noisy environment. In most of the cases the noise source is unknown and hence possess a major difficulty in the filtering operation. In this paper we present an error-correction based learning approach for iterative filtering. A new FIR filter is designed in which the filter coefficients are updated based on Widrow-Hoff rule. Unlike the standard filter the proposed filter has the ability to remove noise without the a priori knowledge of the noise. Experimental result shows that the proposed filter efficiently removes the noise and preserves the edges in the image. We demonstrate the capability of the proposed algorithm by testing it on standard images infected by Gaussian noise and on a real time video containing inherent noise. Experimental result shows that the proposed filter is better than some of the existing standard filters

A DCT Based Filtering of Biomedical Images

Image filtering techniques have numerous potential applications in biomedical imaging and image processing. The design of filters largely depends on the a-priori knowledge about the type of noise corrupting the image and image features. This makes the standard filters to be application and image specific. The most popular filters such as average, Gaussian and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design filters based on discrete cosine transform (DCT) is proposed in this study for optimal medical image filtering. This algorithm exploits the better energy compaction property of DCT and re-arrange these coefficients in a wavelet manner to get the better energy clustering at desired spatial locations. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions.

Voltage and Temperature-Aware SSTA Using Neural Network Delay Model

With the emergence of voltage scaling as one of the most powerful power reduction techniques, it has been important to support voltage scalable statistical static timing analysis (SSTA) in deep submicrometer process nodes. In this paper, we propose a single delay model of logic gate using neural network which comprehensively captures process, voltage, and temperature variation along with input slew and output load. The number of simulation programs with integrated circuit emphasis (SPICE) required to create this model over a large voltage and temperature range is found to be modest and 4x less than that required for a conventional table-based approach with comparable accuracy. We show how the model can be used to derive sensitivities required for linear SSTA for an arbitrary voltage and temperature. Our experimentation on ISCAS 85 benchmarks across a voltage range of 0.9-1.1V shows that the average error in mean delay is less than 1.08% and average error in standard deviation is less than 2.85%. The errors in predicting the 99% and 1% probability point are 1.31% and 1%, respectively, with respect to SPICE. The two potential applications of voltage-aware SSTA have been presented, i.e., one for improving the accuracy of timing analysis by considering instance-specific voltage drops in power grids and the other for determining optimum supply voltage for target yield for dynamic voltage scaling applications.

Oxygen content of liquid cobalt in equilibrium with CoO.(1+x)Al2O3 and -Al2O3

The oxygen concentration of liquid cobalt in equilibrium with cobalt aluminate and a-alumina has been measured by suction sampling and crucible quenching techniques at temperatures between 1770 and 1975 K. Experiments were made with cobalt of high and low initial oxygen contents, and with and without the addition of cobalt aluminate. The effect of temperature on the equilibrium oxygen content is represented by the equation, log (at.% 0) = -10,4001T(K) + 4.64 (±0.008). The composition of the spinel phase, CoO.(1+x)AI20 3, saturated with alumina, has been determined by electron probe microanalysis. The values of x are 0.22 at 1770 Kand 0.28 at 1975 K. The oxygen potential corresponding to the three-phase equilibrium between cobalt, aluminate and alumina, and the standard Gibbs' energy of formation of nonstoichiometric cobalt aluminate are evaluated by combining the results of this study with recently published data on the activity of oxygen in liquid cobalt. Implications of the present results to aluminium deoxidation of liquid cobalt are discussed.

Solubility and activity of oxygen in liquid nickel in equilibrium with -Al2O3 and NiO.(1+x)Al2O3

The limiting solubility of oxygen in liquid nickel in equilibrium withα-alumina and nickel aluminate has been measured by inert gas fusion analysis of suction samples in the temperature range 1730 to 1975 K. The corresponding oxygen potential has been monitored by a solid electrolyte cell consisting of calcia stabilized zirconia as the electrolyte and Mo + MoO2 as the reference electrode. The results can be summarized by the following equations: log(at. pct O) = \frac - 10,005T + 4.944 ( ±0.015)log(atpctO)=T−10005+4944(0015) % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn DmO2 /4.606RT = log P O2 1/2 = \frac - 13,550T + 4.411 ( ±0.009)O24606RT=logPO212=T−13550+4411(0009) From simultaneous measurements of the potential and concentration of oxygen in melts, not in thermodynamic equilibrium with alumina and aluminate phases, information on the composition dependence of the activity coefficient and the standard free energy of solution of oxygen is obtained. For the reaction, $\frac{1}{2} O_2 \to \underset{\raise0.3em\hbox{$Missing close brace ΔG o = -72,930 - 7.11T (±840) J gr.at.–1 = + 0.216 at. pct OlogfO=T−500+0216atpctO where the standard state for dissolved oxygen is that which makes the value of activity equal to the concentration (in at. pct) in the limit as concentration approaches zero. The oxygen solubility in liquid nickel in equilibrium with solid NiO, evaluated from thermodynamic data, is compared with information reported in the literature. Implications of the results to the deoxidation equilibria of aluminum in nickel are discussed.