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.

On a programmable signal processor for VLSI

This paper presents a method of designing a programmable signal processor based on a bit parallel matrix vector matrix multiplier (linear transformer). The salient feature of this design is that the efficiency of the direct vector matrix multiplier is improved and VLSI design is made much simpler by trading off the more expensive arithematic operation (multiplication) for 'cheaper' manipulation (addition/subtraction) of the data.

A PPCA based non-parametric modeling and retrieval of PD signal buried in excessive noise

The problem of on-line recognition and retrieval of relatively weak industrial signals such as partial discharges (PD), buried in excessive noise, has been addressed in this paper. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) due to the overlapping broad band frequency spectrum of PI and PD pulses. Therefore, on-line, onsite, PD measurement is hardly possible in conventional frequency based DSP techniques. The observed PD signal is modeled as a linear combination of systematic and random components employing probabilistic principal component analysis (PPCA) and the pdf of the underlying stochastic process is obtained. The PD/PI pulses are assumed as the mean of the process and modeled instituting non-parametric methods, based on smooth FIR filters, and a maximum aposteriori probability (MAP) procedure employed therein, to estimate the filter coefficients. The classification of the pulses is undertaken using a simple PCA classifier. The methods proposed by the authors were found to be effective in automatic retrieval of PD pulses completely rejecting PI.

A general construction of space-time trellis codes for PSK signal sets

The diversity order and coding gain are crucial for the performance of a multiple antenna communication system. It is known that space-time trellis codes (STTC) can be used to achieve these objectives. In particular, we can use STTCs to obtain large coding gains. Many attempts have been made to construct STTCs which achieve full-diversity and good coding gains, though a general method of construction does not exist. Delay diversity code (rate-1) is known to achieve full-diversity, for any number of transmit antennas and any signal set, but does not give a good coding gain. A product distance code based delay diversity scheme (Tarokh, V. et al., IEEE Trans. Inform. Theory, vol.44, p.744-65, 1998) enables one to improve the coding gain and construct STTCs for any given number of states using coding in conjunction with delay diversity; it was stated as an open problem. We achieve such a construction. We assume a shift register based model to construct an STTC for any state complexity. We derive a sufficient condition for this STTC to achieve full-diversity, based on the delay diversity scheme. This condition provides a framework to do coding in conjunction with delay diversity for any signal constellation. Using this condition, we provide a formal rate-1 STTC construction scheme for PSK signal sets, for any number of transmit antennas and any given number of states, which achieves full-diversity and gives a good coding gain.

Towards formal verification of analog mixed signal designs using SPICE circuit simulation traces

An extension to a formal verification approach of hybrid systems is proposed to verify analog and mixed signal (AMS) designs. AMS designs can be formally modeled as hybrid systems and therefore lend themselves to the formal analysis and verification techniques applied to hybrid systems. The proposed approach employs simulation traces obtained from an actual design implementation of AMS circuit blocks (for example, in the form of SPICE netlists) to carry out formal analysis and verification. This enables the same platform used for formally validating an abstract model of an AMS design, to be also used for validating its different refinements and design implementation; thereby, providing a simple route to formal verification at different levels of implementation. The feasibility of the proposed approach is demonstrated with a case study based on a tunnel diode oscillator. Since the device characteristic of a tunnel diode is highly non-linear with a negative resistance region, dynamic behavior of circuits in which it is employed as an element is difficult to model, analyze and verify within a general hybrid system formal verification tool. In the case study presented the formal model and the proposed computational techniques have been incorporated into CheckMate, a formal verification tool based on MATLAB and Simulink-Stateflow Framework from MathWorks.

Role of Nonplanar Peptide Unit in Regular Polypeptide Helices - New Model for Pply-Beta-Benzyl-L-Aspartate

The effect of non-planarity of the peptide unit on helical structures stabilized by intrachain hydrogen bonds is discussed. While the present calculations generally agree with those already reported in the literature for right-handed helical structures, it is found that the most stable left-handed structure is a novel helix, called the delta-helix. Its helical parameters are close to these reported for poly-beta-benzyl-L -aspartate. Conformational energy calculations show that poly-beta-benzyl-L -aspartate with the delta-helical structure is considerably more stable than the structure it is generally believed to take up (the omega-helix) by about 15 kcal/mol-residue.

15-deoxyspergualin hinders physical interaction between basic residues of transit peptide in PfENR and Hsp70-1

The apicoplast of Plasmodium harbors several metabolic pathways. The enzymes required to perform these reactions are all nuclearly encoded and apicoplast targeted (NEAT) proteins. Plasmodium falciparum Enoyl-ACP Reductase (PfENR) is one such NEAT protein. The NEAT proteins have a transit peptide which is required for crossing the membranes of apicoplast. We studied the importance of basic residues like Arginine and Lysine within the transit peptide. Previous studies have suggested that all basic residues are essential for apicoplast trafficking. In this study, we demonstrate that only some of these residues are essential (K44, R48, K51, and R52), whereas others are dispensable (R40, K42, and K49). On mutating these specific residues, PfENR is not imported into the apicoplast and is mislocalized to the cytoplasm. We also demonstrate that these residues are also crucial for interaction with Hsp70-1, implying that interactions of Lysine 44, Arginine 48, Lysine 51, and Arginine 52 of the transit peptide with PfHsp70-1 are required for apicoplast trafficking. 15-Deoxyspergualin, which has earlier been proposed to interact with EEVD motif of PfHsp70-1 hinders the physical interaction between these cationic residues of PfENR and Hsp70-1. Hence, we propose that in the transport competent state of NEAT proteins some specific positively charged amino acids in the transit peptide interact with PfHsp70-1, and this interaction is essential for apicoplast targeting.

A Long Memory Process Based Parametric Modeling and Recognition of PD Signal

We address the problem of recognition and retrieval of relatively weak industrial signal such as Partial Discharges (PD) buried in excessive noise. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) which has similar time-frequency characteristics as PD pulse. Therefore conventional frequency based DSP techniques are not useful in retrieving PD pulses. We employ statistical signal modeling based on combination of long-memory process and probabilistic principal component analysis (PPCA). An parametric analysis of the signal is exercised for extracting the features of desired pules. We incorporate a wavelet based bootstrap method for obtaining the noise training vectors from observed data. The procedure adopted in this work is completely different from the research work reported in the literature, which is generally based on deserved signal frequency and noise frequency.