On a Ratio of Functions of Exponential Random Variables and Some Applications

Consider L independent and identically distributed exponential random variables (r.vs) X-1, X-2 ,..., X-L and positive scalars b(1), b(2) ,..., b(L). In this letter, we present the probability density function (pdf), cumulative distribution function and the Laplace transform of the pdf of the composite r.v Z = (Sigma(L)(j=1) X-j)(2) / (Sigma(L)(j=1) b(j)X(j)). We show that the r.v Z appears in various communication systems such as i) maximal ratio combining of signals received over multiple channels with mismatched noise variances, ii)M-ary phase-shift keying with spatial diversity and imperfect channel estimation, and iii) coded multi-carrier code-division multiple access reception affected by an unknown narrow-band interference, and the statistics of the r.v Z derived here enable us to carry out the performance analysis of such systems in closed-form.

18-Bit binary inductive voltage divider for self balancing ac bridge applications

The constructional details of an 18-bit binary inductive voltage divider (IVD) for a.c. bridge applications is described. Simplified construction with less number of windings, interconnection of winding through SPDT solid state relays instead of DPDT relays, improves reliability of IVD. High accuracy for most precision measurement achieved without D/A converters. The checks for self consistency in voltage division shows that the error is less than 2 counts in 2(18).

A Sub-Nyquist Sampling Method For Computing The Level-crossing-times Of An Analog Signal: Theory And Applications

We address the problem of computing the level-crossings of an analog signal from samples measured on a uniform grid. Such a problem is important, for example, in multilevel analog-to-digital (A/D) converters. The first operation in such sampling modalities is a comparator, which gives rise to a bilevel waveform. Since bilevel signals are not bandlimited, measuring the level-crossing times exactly becomes impractical within the conventional framework of Shannon sampling. In this paper, we propose a novel sub-Nyquist sampling technique for making measurements on a uniform grid and thereby for exactly computing the level-crossing times from those samples. The computational complexity of the technique is low and comprises simple arithmetic operations. We also present a finite-rate-of-innovation sampling perspective of the proposed approach and also show how exponential splines fit in naturally into the proposed sampling framework. We also discuss some concrete practical applications of the sampling technique.

A novel property of an Auto-Correlation Sequence and some Applications

In this article, we use some spectral properties of polynomials presented in 1] and map an auto-correlation sequence to a set of Line Spectral Frequencies(LSFs) and reflection coefficients. This novel characterization of an auto-correlation sequence is used to obtain a lattice structure of a Linear-Phase(LP) FIR filter.

Decision tree design and applications in speech processing

The design and operation of the minimum cost classifier, where the total cost is the sum of the measurement cost and the classification cost, is computationally complex. Noting the difficulties associated with this approach, decision tree design directly from a set of labelled samples is proposed in this paper. The feature space is first partitioned to transform the problem to one of discrete features. The resulting problem is solved by a dynamic programming algorithm over an explicitly ordered state space of all outcomes of all feature subsets. The solution procedure is very general and is applicable to any minimum cost pattern classification problem in which each feature has a finite number of outcomes. These techniques are applied to (i) voiced, unvoiced, and silence classification of speech, and (ii) spoken vowel recognition. The resulting decision trees are operationally very efficient and yield attractive classification accuracies.

A novel space cloth using resistor grid network for radar absorbers in stealth applications

We report novel resistor grid network based space cloth for application in single and multi layer radar absorbers. The space cloth is analyzed and relations are derived for the sheet resistance in terms of the resistor in the grid network. Design curves are drawn using MATLAB and the space cloth is analyzed using HFSS™ software in a Salisbury screen for S, C and X bands. Next, prediction and simulation results for a three layer Jaumann absorber using square grid resistor network with a Radar Cross Section Reduction (RCSR) of -15 dB over C, X and Ku bands is reported. The simulation results are encouraging and have led to the fabrication of prototype broadband radar absorber and experimental work is under progress.

Dual enzyme responsive microcapsules simulating an ``OR'' logic gate for biologically triggered drug delivery applications

Hollow microcapsules capable of disintegrating in response to dual biological stimuli have been synthesized from two FDA approved drug molecules. The capsules fabricated from protamine and chondroitin sulphate disintegrate in the presence of either trypsin or hyaluronidase enzymes, which are documented to be simultaneously over-expressed under some pathological conditions.

An electrochemical method for the synthesis of few layer graphene sheets for high temperature applications

We demonstrate an electrochemical technique for the large scale synthesis of high quality few layer graphene sheets (FLGS) directly from graphite using oxalic acid (a weak acid) as the electrolyte. One of the interesting observations is that the FLGS are stable at least up to 800 degrees C and hence have potential application in solid oxide fuel cells as a gas diffusion layer.

Adaptive executions of hyperbolic block-structured AMR applications on GPU systems

A block-structured adaptive mesh refinement (AMR) technique has been used to obtain numerical solutions for many scientific applications. Some block-structured AMR approaches have focused on forming patches of non-uniform sizes where the size of a patch can be tuned to the geometry of a region of interest. In this paper, we develop strategies for adaptive execution of block-structured AMR applications on GPUs, for hyperbolic directionally split solvers. While effective hybrid execution strategies exist for applications with uniform patches, our work considers efficient execution of non-uniform patches with different workloads. Our techniques include bin-packing work units to load balance GPU computations, adaptive asynchronism between CPU and GPU executions using a knapsack formulation, and scheduling communications for multi-GPU executions. Our experiments with synthetic and real data, for single-GPU and multi-GPU executions, on Tesla S1070 and Fermi C2070 clusters, show that our strategies result in up to a 3.23 speedup in performance over existing strategies.