Theoretical investigation of the quantum noise in ghost imaging

Ghost imaging is a method to nonlocally image an object by transmitting pairs of entangled photons through the object and a reference optical system respectively. We present a theoretical analysis of the quantum noise in this imaging technique. The dependence of the noise on the properties of the apertures in the imaging system are discussed and demonstrated with a numerical example. For a given source, the resolution and the signal-to-noise ratio cannot be improved at the same time

Parameter Estimation of Switched Hammerstein Systems

This paper deals with the parameter estimation problem of the Single-Input-Single-Output (SISO) switched Hammerstein system. Suppose that the switching law is arbitrary but can be observed online. All subsystems are parameterized and the Recursive Least Squares (RLS) algorithm is applied to estimate their parameters. To overcome the difficulty caused by coupling of data from different subsystems, the concept "intrinsic switch" is introduced. Two cases are considered: i) The input is taken to be a sequence of independent identically distributed (i.i.d.) random variables when identification is the only purpose; ii) A diminishingly excited signal is superimposed on the control when the adaptive control law is given. The strong consistency of the estimates in both cases is established and a simulation example is given to verify the theoretical analysis.Comment: 16 pages, 3 figures; Accepted for publication by Acta Mathematicae Applicatae Sinica (http://link.springer.com/journal/10255

Scaling Speech Enhancement in Unseen Environments with Noise Embeddings

We address the problem of speech enhancement generalisation to unseen environments by performing two manipulations. First, we embed an additional recording from the environment alone, and use this embedding to alter activations in the main enhancement subnetwork. Second, we scale the number of noise environments present at training time to 16,784 different environments. Experiment results show that both manipulations reduce word error rates of a pretrained speech recognition system and improve enhancement quality according to a number of performance measures. Specifically, our best model reduces the word error rate from 34.04% on noisy speech to 15.46% on the enhanced speech. Enhanced audio samples can be found in https://speechenhancement.page.link/samples

Binary Nonlinearization of the Super Akns System Under an Implicit Symmetry Constraint

For the super AKNS system, an implicit symmetry constraint between the potentials and the eigenfunctions is proposed. After introducing some new variables to explicitly express potentials, the super AKNS system is decomposed into two compatible finite-dimensional super systems (x-part and $t_n$-part). Furthermore, we show that the obtained super systems are integrable super Hamiltonian systems in supersymmetry manifold $\mathbb{R}^{4N+2|2N+2}$.Comment: 10 pages, 5 figures, to appear in Journal of Physics