Shiv Nadar University

About: Shiv Nadar University is a education organization based out in Dadri, Uttar Pradesh, India. It is known for research contribution in the topics: Population & Graphene. The organization has 1015 authors who have published 1924 publications receiving 18420 citations.

Mel frequency cepstral coefficients based text independent Automatic Speaker Recognition using matlab

Abstract: Speech feature extraction is the most significant step in any Automatic speaker recognition system. In the last 60 years a lot of research has gone into parametric representation of these speech features. Several techniques are currently being used for Automatic Speaker Recognition. Yet Automatic Speaker Recognition still remains a confront mainly due to variations in speaker's vocal tract with time and health, varying environmental conditions, disparities in the behavior and quality of speech recorders etc. MFCC is a extensively used technique in Automatic speaker recognition. In this paper the performance of MFCC technique was evaluated in a quiet environment. A speaker database containing 30 male and 30 female speakers was created. Two separate experiments were conducted for the performance evaluation of MFCC technique when applied to K means clustering. In the first case the speech features were directly matched. In the second case a VQ codebook was created by clustering the training features of these 60 speakers. A distortion easure based on the minimum Euclidean distance was used for speaker recognition. The failure rate of speaker recognition in first ase was found to be was found to be 10% while in the second case as found to be 14%. Matlab-7.10.0 was used for this study.

Allocation to Anchor Investors, Underpricing, and the After‐Market Performance of IPOs

Abstract: We study bidding by anchor investors in a two-stage initial public offering (IPO) process and document a negative, causal relation between allocation to anchor investors and underpricing. We find that anchor investors are likely to invest in hard-to-place offerings characterized by valuation uncertainty. We also document a positive relation between allocation to reputed anchor investors and returns up to lock-up expiration. Our evidence provides support for information revelation and targeting specific investors’ theories of book building. Anchor-backed IPOs earn superior returns mainly due to monitoring. Who bids in an IPO seems to matter just as particular types of bids do.

Mapping generalized Jaynes–Cummings interaction into correlated finite-sized systems

Abstract: We consider a generalized Jaynes–Cummings model of a two-level atom interacting with a multimode nondegenerate coherent field. The sum of the mode frequencies is equal to the two-level transition frequency, creating the resonance condition. The intermediate levels associated with the multiphoton process are adiabatically eliminated using the non-resonant conditions for these transitions. Under such general conditions, the infinite atom–multiphoton interaction is effectively mapped onto an equivalent reduced 2 ×2 bipartite qubit system that facilitates the study of the nonclassical features of the interaction using known information-theoretic measures. We observe that the bipartite pure system is highly entangled as quantified by its entanglement of formation. Furthermore, it is shown that the dynamics of the mapped system can be generated using optically truncated, quantum scissored states that reduce the infinite atom–multiphoton interaction to a finite 2 × k system, where k is a suitable truncation number. This allows us to introduce atomic dephasing and study the mixed state dynamics, characterized by the decay of quantum correlations such as quantum discord, which is observed to be more robust than entanglement. The quantum correlation dynamics of the dissipative system qualitatively complements the behaviour of collapse and revival of the Rabi oscillations in the system. The effective mapping of the composite system proves to be an efficient tool for measuring information-theoretic properties.