For a sinusoidal signal, buried in white Gaussian noise, as an input to a parallel array of bistable oscillators, it is reported that conditions exist where the signal-to-noise ratio gain exceeds unity, for both subthreshold and suprathreshold sinusoids. The performance of infinite arrays is closely approached by finite arrays of moderate size, representing a novel method of applying the stocha...

We demonstrate a new simultaneous normalized detection technique for fluorescence detection of ultracold atoms in a superposition of ground-state hyperfine levels. Using this technique we observe atom shot-noise limited detection signal-to-noise ratios in excess of 7800:1 per shot and 14400:1 in 1 s.

* Perception of English voiceless fricatives by Japanese and English native listeners under various signal-to-noise ratios, by MASUDA, Hinako and ARAI, Takayuki (Sophia University).

An important issue in the analysis of fMRI is how to account for the spatial smoothness of activated regions. In this article a method is proposed to accomplish this by modeling activated regions with Gaussian shapes. Hypothesis tests on the location, spatial extent, and amplitude of these regions are performed instead of hypothesis tests of individual voxels. This increases power and eases int...

Executive Summary. Both dividend yields and past returns have predictive power for P/E ratios; hence they can be used as tools in forming a market timing and asset allocation strategy in stock markets. This study examines the extent to which changes in real estate returns, reflected in changes of property value and dividend yields, can have great effects on P/E ratios. The study is confined to ...

In all methods of image denoising there is a problem always exists that is how to distinguish noise and edge. Now wavelet and contourlet are main tools in image denoising, but threshold is the key in wavelet and contourlet denoising. In order to distinguish noise and edge well, most methods in wavelet denoising are about the improvement of threshold. Aiming to resolve this problem, a new method...

A novel patch based adaptive diffusion method is presented for image denoising. This is done with the purpose of locally and feature adaptive diffusion and for attaining patch-wise best peak signal to noise ratio. Our framework uses over-segmentation method to segment the image in to sensible regions and then diffusion of each segment/region to obtain the near-optimal solution and iterates to a...

The present paper, proposes an efficient denoising algorithm which works well for images corrupted with Gaussian and speckle noise. The denoising algorithm utilizes the alexander fractional integral filter which works by the construction of fractional masks window computed using alexander polynomial. Prior to the application of the designed filter, the corrupted image is decomposed using symlet...

Digital image plays a vital role in the early detection of cancers, such as prostate cancer, breast cancer, lungs cancer, cervical cancer. Ultrasound imaging method is also suitable for early detection of the abnormality of fetus. The accurate detection of region of interest in ultrasound image is crucial. Since the result of reflection, refraction and deflection of ultrasound waves from differ...

Radar target identification using high resolution range profile (HRRP), the target length is an important feature due to that it can reduce the time of identification and mitigate noise redundancy. Traditional threshold methods with the different operators are highly sensitive to noise. In this paper, we proposed an adaptive difference operator for target length feature extraction from HRRP. Ex...