Empirical mode decomposition (EMD) is a powerful algorithm that decomposes signals as a set of intrinsic mode function (IMF) based on the signal complexity. In this study, partial reconstruction of IMF acting as a filter was used for noise reduction in ECG. An improved algorithm, ensemble EMD (EEMD), was used for the first time to improve the noise-filtering performance, based on the mode-mixin...

Abstract— A CDMA unslotted ALOHA system using MMSE multi-user detection is proposed. In CDMA unslotted ALOHA system, a user station can transmit a packet asynchronously, and so the number of simultaneously transmitted packets fluctuates moment by moment. This fluctuation affects the performance of the MMSE multi-user detection. At first, we employ the Wiener filter detector assuming perfect inf...

In this paper a time-frequency estimator for enhancement of noisy speech signals in the DFT domain is introduced. This estimator is based on modeling the time-varying correlation of the temporal trajectories of the short time (ST) DFT components of the noisy speech signal using autoregressive (AR) models. The timevarying trajectory of the DFT components of speech in each channel is modeled by a...

We propose a novel speech enhancement technique based on the hypothesized Wiener filter (HWF) methodology. The proposed HWF algorithm selects a filter for enhancing the input noisy signal by first ‘hypothesizing’ a set of filters and then choosing the most appropriate one for the actual filtering. We show that the proposed HWF can intrinsically offer superior performance to conventional Wiener ...

In this paper, we propose a dual-microphone target-directional speech enhancement system utilizing target-to-non-target directional signal ratio (TNR) based on dual-microphone phase differences in adverse noise environments. One of the important issues associated with multi-microphone speech enhancement methods is the effective utilization of spatial cues such as phase differences for target-sp...

The restoration achieved on the basis of a Wiener scheme is an optimum since the restoration filter is the outcome of a minimisation process. Moreover, the Wiener restoration approach requires the estimation of some parameters related to the original image and the noise, as well as knowledge about the PSF function. However, in a real restoration problem, we may not possess accurate values of th...

We examine the question of determining the "best" linear filter, in an expected squared error sense, for a signal generated by stochastic linear differential equation on a Hilbert space. Our results, which extend the development in Kalman and Bucy (1960), rely heavily on the integration theory for Banach-space-valued functions of Dunford and Schwartz (1958). In order to derive the Kalman-Bucy f...

Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose . In this paper a new image restoration scheme i...

Image restoration is the process of reconstruction or recovering an image that has been corrupted by some degradation phenomenon. Degradation may occur due to motion blur, Gaussian blur, noise and camera mismatch. In this paper corrupted image have been recovered using Modified Lucy Richardson algorithm in the presence of Gaussian blur and motion blur. The performance of this algorithm has been...

2433 All Rights Reserved © 2016 IJARECE  Abstract— Speech plays an important role in any communication system. An unwanted signal, known as noise, is added to speech and degrades the quality of signal. There are many speech enhancement techniques used for noise suppression such as spectral subtraction, wiener filtering, decision directed method etc. In this paper, we study some speech enhancem...