Speech segmentation using extrema based signal track length measure

We introduce a novel temporal feature of a signal, namely extrema-based signal track length (ESTL) for the problem of speech segmentation. We show that ESTL measure is sensitive to both amplitude and frequency of the signal. The short-time ESTL (ST_ESTL) shows a promising way to capture the significant segments of speech signal, where the segments correspond to acoustic units of speech having distinct temporal waveforms. We compare ESTL based segmentation with ML and STM methods and find that it is as good as spectral feature based segmentation, but with lesser computational complexity.

A Combinatorial Family of Near Regular LDPC Codes

An elementary combinatorial Tanner graph construction for a family of near-regular low density parity check (LDPC) codes achieving high girth is presented. These codes are near regular in the sense that the degree of a left/right vertex is allowed to differ by at most one from the average. The construction yields in quadratic time complexity an asymptotic code family with provable lower bounds on the rate and the girth for a given choice of block length and average degree. The construction gives flexibility in the choice of design parameters of the code like rate, girth and average degree. Performance simulations of iterative decoding algorithm for the AWGN channel on codes designed using the method demonstrate that these codes perform better than regular PEG codes and MacKay codes of similar length for all values of Signal to noise ratio.

Simulation of RNA silencing pathway for time-dependent transgene transcription rate

The synthesis of dsRNA is analyzed using a pathway model with amplifications caused by the aberrant RNAs. The transgene influx rate is assumed time-decaying considering the fact that the number of transgenes can not be infinite. The dynamics of the transgene induced RNA silencing is investigated using a system of coupled nonautonomous ordinary nonlinear differential equations which describe the model phenomenologically. The silencing phenomena are detected after a period of transcription. Important contributions of certain parameters are discussed with several numerical examples.

Training-Symbol Embedded, High-Rate, Single-Symbol ML-Decodable, Distributed STBCs for Relay Networks

Distributed space-time block codes (DSTBCs) from complex orthogonal designs (CODs) (both square and nonsquare), coordinate interleaved orthogonal designs (CIODs), and Clifford unitary weight designs (CUWDs) are known to lose their single-symbol ML decodable (SSD) property when used in two-hop wireless relay networks using amplify and forward protocol. For such networks, in this paper, three new classes of high rate, training-symbol embedded (TSE) SSD DSTBCs are constructed: TSE-CODs, TSE-CIODs, and TSE-CUWDs. The proposed codes include the training symbols inside the structure of the code which is shown to be the key point to obtain the SSD property along with the channel estimation capability. TSE-CODs are shown to offer full-diversity for arbitrary complex constellations and the constellations for which TSE-CIODs and TSE-CUWDs offer full-diversity are characterized. It is shown that DSTBCs from nonsquare TSE-CODs provide better rates (in symbols per channel use) when compared to the known SSD DSTBCs for relay networks. Important from the practical point of view, the proposed DSTBCs do not contain any zeros in their codewords and as a result, antennas of the relay nodes do not undergo a sequence of switch on/off transitions within every codeword, and, thus, avoid the antenna switching problem.

Design of MMSE filterbank precoder and equalizer for MIMO frequency selective channels

In this paper, we consider the problem of designing minimum mean squared error (MMSE) filterbank precoder and equalizer for multiple input multiple output (MIMO) frequency selective channels. We derive the conditions to be satisfied by the optimal precoder-equalizer pair, and provide an iterative algorithm for solving them. The optimal design is very general, in that it is not constrained by channel dimensions, channel order, channel rank, or the input constellation. We also discuss some pertinent difierences between the filterbank approach and the space-time approach to the design of optimal precoder and equalizer. Simulation results demonstrate that the proposed design performs better than the space-time systems while supporting a higher data rate.

Design of a constrained high data rate CDMA system

This paper deals with the design of a high data rate code-division multiple-access (CDMA) system under a speci¯ed jamming mar- gin speci¯cation as well as hardware and band-width limitations. Several choices had to be made in coming up with the design such as specify-ing the number of subcarriers, choice of spread-ing codes and the nature of the modulation.The rationale behind each of the choices made is given. Descriptions of transmitter and receiver are also included. Relevant simulations of cross-correlation are also provided.

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.

Utilizing an ionic liquid for synthesizing a soft matter polymer ``gel'' electrolyte for high rate capability lithium-ion batteries

A cross-linked polymer ``gel'' electrolyte obtained from free radical polymerization of a vinyl monomer (acrylonitrile; AN) in a room temperature ionic liquid electrolyte (N,N-methyl butyl pyrrolidinium-bis (trifluoromethanesulphonyl)imide-lithium bis(trifluoromethanesulphonyl) imide;LiTFSI-[Py(1,4)-TFSI]) for application in high rate capability rechargeable lithium-ion batteries is discussed here. This is a novel alternative compared to the often employed approach of using a molecular liquid as the medium for performing the polymerization reaction. The polymer ``gel'' electrolytes (AN:Py(1,4)-TFSI = 0.16-0.18, w/w) showed remarkable compliable mechanical strength and higher thermal stability compared to LiTFSI-[Py(1,4)-TFSI]. Despite two orders increase in magnitude of viscosity of polymer ``gels'', the room temperature ionic conductivity of the ``gels'' (1.1 x 10(-3)-1.7 x 10(-3) Omega(-1) cm(-1)) were nearly identical to that of the ionic liquid (1.8 x 10(-3) Omega(-1) cm(-1)). The present ``gel'' electrolytes did not exhibit any ageing effects on ionic conductivity similar to the conventional polymer gel electrolytes (e.g. high molecular weight polymer + salt + high dielectric constant molecular solvent). The disorder (ionic liquid) to a relative order (cross-linked polymer electrolyte) transformation does not at all influence the concentration of conducting species. The polymer framework is still able to provide efficient pathways for fast ion transport. Unlike the ionic liquid which is impossible to assemble without a conventional separator in a cell, the polymer ``gel'' electrolyte could be conveniently assembled without a separator in a Li vertical bar lithium iron phosphate (LiFePO(4)) cell. Compared to the ionic liquid, the ``gel'' electrolyte showed exceptional cyclability and rate capability (current density: 35-760 mA g(-1) with LiFePO(4) electronically wired with carbon (amorphous or multiwalled nanotube [MWCNT]).

Bayesian framework and message passing for joint support and signal recovery of approximately sparse signals

In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly sparse signals from noisy measurements can be viewed as a problem of recovery of approximately sparse signals from noiseless measurements, making the approach applicable to strictly sparse signal recovery from noisy measurements. The support recovery embedded in the approach makes it suitable for recovery of signals with same sparsity profiles, as in the problem of multiple measurement vectors (MMV). Simulation results show that the proposed algorithm, termed as JSSR-MP (joint support and signal recovery via message passing) algorithm, achieves performance comparable to that of sparse Bayesian learning (M-SBL) algorithm in the literature, at one order less complexity compared to the M-SBL algorithm.