Kushagra Singhal

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Learning the influence structure of multiple time series data is of great interest to many disciplines. This paper studies the problem of recovering the causal structure in network of multivariate linear Hawkes processes. In such processes, the occurrence of an event in one process affects the probability of occurrence of new events in some other processes.(More)
Removal of Baseline Wander and power line interference plays a significant role in diagnosing most of the cardiac diseases. ECG signals are formed of P wave, QRS complex, and T wave. Techniques available in the literature were mostly based on digital filters, Artificial Neural Network, and other signal processing techniques. All these techniques have their(More)
Source localization using spherical microphone arrays has received attention due to the ease of array processing in the spherical harmonics (SH) domain with no spatial ambiguity. In this paper, we address the issue of near-field source localization using a spherical microphone array. In particular, three methods that jointly estimate the range and bearing(More)
In this paper, a novel method of robust source localization using MUSIC-Group delay (MUSIC-GD) spectrum computed over spherical harmonic components is described. Our earlier work on the MUSIC-GD spectrum has focused on uniform linear array (ULA) and uniform circular array (UCA) for resolving closely spaced speech sources using minimal number of sensors(More)
We consider the problem of performing community detection on a network, while maintaining privacy, assuming that the adversary has access to an auxiliary correlated network. We ask the question “Does there exist a regime where the network cannot be deanonymized perfectly, yet the community structure could be learned?.” To answer this question, we derive(More)
Sparse reconstruction methods have been used extensively for source localization over uniform linear arrays and circular arrays. In this paper a sparse reconstruction method for speech source localization using partial dictionaries over a spherical microphone array is proposed. The source localization method proposed in this work addresses two important(More)
How chaperones interact with protein chains to assist in their folding is a central open question in biology. Obtaining atomistic insight is challenging in particular, given the transient nature of the chaperone-substrate complexes and the large system sizes. Recent single-molecule experiments have shown that the chaperone Trigger Factor (TF) not only binds(More)
The performance of an ICA-Beamforming framework in multi source environments is often limited by the resolution of the direction of arrival (DOA) estimation and by permutation errors. In this paper a framework that addresses these issues, using the MUSIC-Group delay method of DOA estimation has been described. A new cost function defined for this purpose(More)
Percolation based graph matching algorithms rely on the availability of seed vertex pairs as side information to e ciently match users across networks. Although such algorithms work well in practice, there are other types of side information available which are potentially useful to an attacker. In this paper, we consider the problem of matching two(More)
Trigger factor (TF) is a chaperone, found in bacterial cells and chloroplasts, that interacts with nascent polypeptide chains to suppress aggregation. While its crystal structure has been resolved, the solution structure and dynamics are largely unknown. We performed multiple molecular dynamics simulations on Trigger factor in solution, and show that its(More)
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