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In this paper, we aim to present a principled approach to the problem of depth-based complexity characterisation of graphs. Our idea is to decompose graphs into substructures of increasing size, and then to measure the complexity of these substructures using Shannon entropy or von-Neumann entropy. We commence by identifying the dominant vertex in a graph. From the dominant vertex, we construct subgraphs...
Low-density parity-check (LDPC) codes are capacity approaching codes that have rapidly been adopted in modern systems such as the IEEE 802.11n and long term evolution advanced (LTE-A) communications standards. The decoders based on the iterative belief propagation offer exceedingly high performance but unfortunately have high computational complexity. Therefore significant research has focused on...
Recently, music retrieval is getting more and more attentions, especially for the query by humming (QBH), which is straightforward and convenient for usage. However, the difference between humming phrase matching and the precision of singer humming increase the difficulty of retrieval. Apart from retrieval precision, retrieval time is another issue should be taken into consideration. In this paper,...
Quantum detection in an N-dimensional Hilbert space H involves quantum states and corresponding measurement operators which span an r-dimensional subspace U of H, with r<=N. Quantum detection could be restricted to this subspace, but the detection operations performed in U are still redundant, since the kets have N components. By applying the singular-value decomposition to the state matrix, it...
This paper studies noise-predictive maximum-likelihood (NPML) detection in the case where noise prediction is accomplished by infinite, rather than finite, impulse-response filters. Two infinite-impulse-response (IIR) NPML detection methods are described. The first one uses an embedding technique to achieve IIR noise prediction in combination with a detector trellis that represents a channel target...
A nonlinear active noise control (ANC) system based on a couple of low complexity nonlinear networks are developed in this paper. These are the evolutionary computing based feed forward nonlinear network (FFNN) and the evolutionary computing based feed forward recursive nonlinear network (FFRNN). The new method does not require the identification of the secondary path, which not only improves the...
Boundary points detection of clusters is important in image processing, machine learning and so on. We propose a boundary detecting algorithm called BDDTS (Boundary Detection algorithm of clusters based on Dual Threshold Segmentation), which is based on the characteristics of the distribution of boundary points. The algorithm, which firstly accrues to the different cost function values of data points,...
The availability of various photo archives and photo sharing systems made similarity searching much more important because the photos are not usually conveniently tagged. So the photos (images) need to be searched by their content. Moreover, it is important not only to compare images with a query holistically but also to locate images that contain the query as their part. The query can be a picture...
Edge detection is widely applied in digital image processing, especially in segmentation of images. Many of the well-known edge detectors, e.g., Sobel and Canny operator, are based on spatial filtering with a mask around the pixel under detection. In this paper, we propose a very low complexity edge detector that has two operation modes; non-causal mode and causal mode. Though simple in its form,...
In this paper, we propose an improved multi-label approach to classify web pages by genre. Our approach provides a multi-label classification scheme in which a web page can be assigned to more than one genre. To deal with the rapid evolution of web genres, our approach implements an incremental centroid-based classification scheme. Conducted experiments on a multi-labeled corpus of web pages show...
We consider the media-access control problem for nodes with heavy traffic in single-destination wireless networks. We assume that each source transmits in each time slot according to a transmission probability, which is a continuous value between 0 and 1. Our goal is to determine the values of the transmission probabilities so that the network throughput is maximized. In this paper, we show that the...
The problem central to sparse recovery and compressive sensing is that of \emph{stable sparse recovery}: we want a distribution of matrices such that, for any and with probability over $A \in \math cal{A}$, there is an algorithm to recover from with\begin{align} \norm{p}{\hat{x} - x} \leq C \min_{k\text{-sparse } x'}...
This paper analyzes the existing decision tree classification algorithms and finds that these algorithms based on variable precision rough set (VPRS) have better classification accuracies and can tolerate the noise data. But when constructing decision tree based on variable precision rough set, these algorithms have the following shortcomings: the choice of attribute is difficult and the decision...
Ultra-wideband (UWB) is a modern radio technology that works at extremely low energy levels. It is popularly used in short-range, low power and low cost communications such as RFIDs. This paper presents a UWB receiver using energy detection scheme with on-off keying (OOK) modulation. A novel synchronization and detection algorithm called energy offset based scheme is investigated and used in the receiver...
We consider the problem of rate-compatible (RC)-encoder and RC-puncturing of LDPC codes. The proposed encoder is based on a modification of MacKay encoding scheme. The introduced modification enables the application of MacKay scheme for quasi-cyclic (QC) LDPC codes combined with a proposed matrix puncturing scheme based on an also proposed parity-check matrix construction to achieve code-rate compatibility...
The long term prediction (LTP) tool is used in audio compression systems to exploit periodicity in signals. This tool capitalizes on the periodic component of the waveform by selecting a past segment as the basis for prediction of the current frame. However, most audio signals are polyphonic in nature, consisting of a mixture of periodic signals. This renders the LTP suboptimal, as the mixture's period...
Tree search is an important kind of detection method. It can be used in multiple-input multiple-output systems detection and the multi-user detection. In this paper, a novel adjustable reduced metric-first sphere decoding algorithm for tree search has been proposed. By setting a suitable and adjustable threshold, the proposed algorithm cuts nodes whose partial Euclidean distances are larger than it...
The booming of the Internet and its applications, especially, the recent trend in outsourcing databases, fuels the research on symmetrically private information retrieval (SPIR) schemes. In this paper, we propose a fully homomorphic encryption based SPIR scheme in order to further improve the comm-unication cost of SPIR from O((logn)²) to O(logn). Actually, our schemes can be directly used to implement...
The increasing number of ICP variants leads to an explosion of algorithms and parameters. This renders difficult the selection of the appropriate combination for a given application. In this paper, we propose a state-of-the-art, modular, and efficient implementation of an ICP library. We took advantage of the recent availability of fast depth cameras to demonstrate one application example: a 3D pose...
This paper aims to evaluate the accuracy of optical character recognition (OCR) systems on real scanned books. The ground truth e-texts are obtained from the Project Gutenberg website and aligned with their corresponding OCR output using a fast recursive text alignment scheme (RETAS). First, unique words in the vocabulary of the book are aligned with unique words in the OCR output. This process is...
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