Dynamic programming based optimum non-uniform samples for speech reconstruction and coding

Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.

Non-unitary-weight Space-Time Block Codes with Minimum Decoding Complexity

Space-Time Block Codes (STBCs) from Complex Orthogonal Designs (CODs) are single-symbol decodable/symbol-by-symbol decodable (SSD); however, SSD codes are obtainable from designs that are not CODs. Recently, two such classes of SSD codes have been studied: (i) Coordinate Interleaved Orthogonal Designs (CIODs) and (ii) Minimum-Decoding-Complexity (MDC) STBCs from Quasi-ODs (QODs). The class of CIODs have non-unitary weight matrices when written as a Linear Dispersion Code (LDC) proposed by Hassibi and Hochwald, whereas the other class of SSD codes including CODs have unitary weight matrices. In this paper, we construct a large class of SSD codes with nonunitary weight matrices. Also, we show that the class of CIODs is a special class of our construction.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.

Increasing ionic conductivity of polymer-sodium salt complex by addition of a non-ionic plastic crystal

Ionic conductivity and other physico-chemical properties of a soft matter composite electrolyte comprising of a polymer-sodium salt complex and a non-ionic plastic crystal are discussed here. The electrolyte under discussion comprises of polyethyleneoxide (PEO)-sodium triflate (NaCF3SO3) and succinonitrile (SN). Addition of SN to PEO-NaCF3SO3 resulted in significant enhancement in ionic conductivity. At 50% SN concentration (with respect to weight of polymer), the polymer-plastic composite electrolyte room temperature (= 25 degrees C) ionic conductivity was similar to 1.1 x 10(-4) Omega(-1) cm(-1), approximately 45 times higher than PEO-NaCF3SO3. Observations from ac-impedance spectroscopy along with X-ray diffraction, differential scanning calorimetry and Fourier transform inrared spectroscopy strongly suggest the enhancement in the composite is ionicconductivity due to enhanced ion mobility via decrease in crystallinity of PEO. The free standing composite polymer-plastic electrolytes were more compliable than PEO-NaCF3SO3 thus exhibiting no detrimental effects of succinonitrile addition on the mechanical stability of PEO-NaCF3SO3. We propose that the exploratory PEO-NaCF3SO3-SN system.discussed here will eventually be developed as a prototype electrolyte.for sodium-sulfur batteries capable of operating at ambient and.sub-ambient conditions. (C) 2010 Elsevier B.V. All rights reserved.

Non-resonant microwave absorption evidence for intrinsic Josephson coupling in Tl2Ba2CaCu2O8 single crystals

We report the results of our non-resonant microwave absorption (NRMA) studies on single crystals of Tl2Ba2CaCu2O8 (Tl 2212) which reflect the occurrence of intrinsic Josephson coupling in these crystals. We have studied the magnetic field induced microwave absorption at various temperatures from 4.2K to T-c (similar to 104K) using a standard CW EPR spectrometer (H-dc parallel to c). We observe the appearance of a characteristic feature in the NRMA signals similar to the ones observed earlier by us in Bi2Sr2CaCu2O8 (Bi 2212) starting a few degrees below T-c, which on cooling passes through a maximum in intensity before disappearing at a further low temperature. This behaviour is attributed to the appearance, strengthening and disappearance of Josephson response consequent to the temperature dependence of the viscosity of the Josephson medium between the CuO2 superconducting sheets.

Non-periodic tilings in 2-dimensions with 4, 6, 8, 10 and 12-fold symmetries

The two dimensional plane can be filled with rhombuses, so as to generate non-periodic tilings with 4, 6, 8, 10 and 12-fold symmetries. Some representative tilings constructed using the rule of inflation are shown. The numerically computed diffraction patterns for the corresponding tilings are also shown to facilitate a comparison with possible X-ray or electron diffraction pictures.

Low-Complexity Near-ML Decoding of Large Non-Orthogonal STBCs using Reactive Tabu Search

Non-orthogonal space-time block codes (STBC) with large dimensions are attractive because they can simultaneously achieve both high spectral efficiencies (same spectral efficiency as in V-BLAST for a given number of transmit antennas) as well as full transmit diversity. Decoding of non-orthogonal STBCs with large dimensions has been a challenge. In this paper, we present a reactive tabu search (RTS) based algorithm for decoding non-orthogonal STBCs from cyclic division algebras (CDA) having largedimensions. Under i.i.d fading and perfect channel state information at the receiver (CSIR), our simulation results show that RTS based decoding of 12 X 12 STBC from CDA and 4-QAM with 288 real dimensions achieves i) 10(-3) uncoded BER at an SNR of just 0.5 dB away from SISO AWGN performance, and ii) a coded BER performance close to within about 5 dB of the theoretical MIMO capacity, using rate-3/4 turbo code at a spectral efficiency of 18 bps/Hz. RTS is shown to achieve near SISO AWGN performance with less number of dimensions than with LAS algorithm (which we reported recently) at some extra complexity than LAS. We also report good BER performance of RTS when i.i.d fading and perfect CSIR assumptions are relaxed by considering a spatially correlated MIMO channel model, and by using a training based iterative RTS decoding/channel estimation scheme.

Low-Complexity Near-MAP Decoding of Large Non-Orthogonal STBCs Using PDA

Non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) are attractive because they can simultaneously achieve both high spectral efficiencies (same spectral efficiency as in V-BLAST for a given number of transmit antennas) as well as full transmit diversity. Decoding of non-orthogonal STBCs with hundreds of dimensions has been a challenge. In this paper, we present a probabilistic data association (PDA) based algorithm for decoding non-orthogonal STBCs with large dimensions. Our simulation results show that the proposed PDA-based algorithm achieves near SISO AWGN uncoded BER as well as near-capacity coded BER (within 5 dB of the theoretical capacity) for large non-orthogonal STBCs from CDA. We study the effect of spatial correlation on the BER, and show that the performance loss due to spatial correlation can be alleviated by providing more receive spatial dimensions. We report good BER performance when a training-based iterative decoding/channel estimation is used (instead of assuming perfect channel knowledge) in channels with large coherence times. A comparison of the performances of the PDA algorithm and the likelihood ascent search (LAS) algorithm (reported in our recent work) is also presented.

Belief Propagation Based Decoding of Large Non-Orthogonal STBCs

In this paper,we present a belief propagation (BP) based algorithm for decoding non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) having large dimensions. The proposed approachinvolves message passing on Markov random field (MRF) representation of the STBC MIMO system. Adoption of BP approach to decode non-orthogonal STBCs of large dimensions has not been reported so far. Our simulation results show that the proposed BP-based decoding achieves increasingly closer to SISO AWGN performance for increased number of dimensions. In addition, it also achieves near-capacity turbo coded BER performance; for e.g., with BP decoding of 24 x 24 STBC from CDA using BPSK (i.e.,n576 real dimensions) and rate-1/2 turbo code (i.e., 12 bps/Hz spectral efficiency), coded BER performance close to within just about 2.5 dB from the theoretical MIMO capacity is achieved.