Recent technological advances in wireless communications offer new opportunities and challenges for relay network. To enhance system performance, Demodulate-Network Coding (Dm-NC) scheme has been examined at relay node; it works directly to De-map the received signals and after that forward the mixture to the destination. Simulation analysis has been proven that the performance of Dm-NC has sup...

In this paper a novel distributed video coding scheme was proposed based on Heegard-Berger coding theorem, rather than Wyner-Ziv theorem. The main advantage of HB coding is that the decoder can still decode and output a coarse reconstruction, even if side information degrade or absent. And if side information present or upgrade at decoder, a better reconstruction can be achieved. This robust fe...

Sparse coding is a method for nding a representation of data in which each of the components of the representation is only rarely signiicantly active. Such a representation is closely related to the techniques of independent component analysis and blind source separation. In this paper, we investigate the application of sparse coding for image feature extraction. We show how sparse coding can b...

Feature coding and pooling as a key component of image retrieval have been widely studied over the past several years. Recently sparse coding with max-pooling is regarded as the state-of-the-art for image classification. However there is no comprehensive study concerning the application of sparse coding for image retrieval. In this paper, we first analyze the effects of different sampling strat...

This paper investigates use of a machine learnt model for recognition of individually words spoken in Urdu language. Speech samples from many different speakers were utilized for modeling. Original time-domain samples are normalized and pre-processed by applying discrete Fourier transformation for speech feature extraction. In frequency domain, high degree of correlation was found for the same ...

The purpose of this research was to explore how adult users interact and learn during an interactive computer-based simulation supplemented with brief multimedia explanations of the content. A total of 52 college students interacted with a computer-based simulation of Newton’s laws of motion in which they had control over the motion of a simple screen object—an animated ball. Two simulation con...

We suggest a new approach to optimize the learning of sparse features under the constraints of explicit transformation symmetries imposed on the set of feature vectors. Given a set of basis feature vectors and invariance transformations, from each basis feature a family of transformed features is generated. We then optimize the basis features for optimal sparse reconstruction of the input patte...

In recent years, designing the coding and pooling structures in layered networks has been shown to be a useful method for learning high-level feature representations for visual data. Yet, such learning structures have not been extensively studied for audio signals. In this paper, we investigate different pooling strategies based on the sparse coding scheme and propose a temporal pyramid pooling...