The windowed interpolation DFT methods have been utilized to estimate the parameters of a single frequency and multi-frequency signal. Nevertheless, they do not work well for the real-valued sinusoids with closely spaced positive- and negative- frequency. In this paper, we describe a novel three-point windowed interpolation DFT method for frequency measurement of real-valued sinusoid signal. The exact representation of the windowed DFT with maximum sidelobe decay window (MSDW) is constructed. The spectral superposition of positive- and negative-frequency is considered and calculated to improve the estimation performance. The simulation results match with the theoretical values well. In addition, computer simulations demonstrate that the proposed algorithm provides high estimation accuracy and good noise suppression capability.

Sparse code multiple access (SCMA) based on the message passing algorithm (MPA) for multiuser detection is a competitive non-orthogonal multiple access technique for fifth-generation wireless communication networks Among the existing multiuser detection schemes for uplink (UP) SCMA systems, the serial MPA (S-MPA) scheme, where messages are updated sequentially, generally converges faster than the conventional MPA (C-MPA) scheme, where all messages are updated in a parallel manner. In this paper, the optimization of message scheduling in the S-MPA scheme is proposed. Firstly, some statistical results for the probability density function (PDF) of the received signal are obtained at various signal-to-noise ratios (SNR) by using the Monte Carlo method. Then, based on the non-orthogonal property of SCMA, the data mapping relationship between resource nodes and user nodes is comprehensively analyzed. A partial codeword transmission of S-MPA (PCTS-MPA) with threshold decision scheme of PDF is proposed and verified. Simulations show that the proposed PCTS-MPA not only reduces the complexity of MPA without changing the bit error ratio (BER), but also has a faster convergence than S-MPA, especially at high SNR values.

Feature visualization is of great significances in volume visualization, and feature extraction has been becoming extremely popular in feature visualization. While precise definition of features is usually absent which makes the extraction difficult. This paper employs probability density function (PDF) as statistical property, and proposes a statistical property guided approach to extract features for volume data. Basing on feature matching, it combines simple liner iterative cluster (SLIC) with Gaussian mixture model (GMM), and could do extraction without accurate feature definition. Further, GMM is paired with a normality test to reduce time cost and storage requirement. We demonstrate its applicability and superiority by successfully applying it on homogeneous and non-homogeneous features.

There are often low contrast Mycobacterium tuberculosis (MTB) objects in the MTB images. Based on improved histogram equalization (HE), a framework of contrast enhancement is proposed to increase the contrast of MTB images. Our proposed algorithm was compared with the traditional HE and the weighted thresholded HE. The experimental results demonstrate that our proposed algorithm has better performance in contrast enhancement, artifacts suppression, and brightness preserving for MTB images.

Blind source separation (BSS) techniques are required for various signal decomposing issues. Independent component analysis (ICA), assuming only a statistical independence among stochastic source signals, is one of the most useful BSS tools because it does not need a priori information on each source. However, there are many requirements for decomposing multiple deterministic signals such as complex sinusoidal signals with different frequencies. These requirements may include pulse compression or clutter rejection. It has been theoretically shown that an ICA algorithm based on maximizing non-Gaussianity successfully decomposes such deterministic signals. However, this ICA algorithm does not maintain a sufficient separation performance when the frequency difference of the sinusoidal waves becomes less than a nominal frequency resolution. To solve this problem, this paper proposes a super-resolution algorithm for complex sinusoidal signals by extending the maximum likelihood ICA, where the probability density function (PDF) of a complex sinusoidal signal is exploited as a priori knowledge, in which the PDF of the signal amplitude is approximated as a Gaussian distribution with an extremely small standard deviation. Furthermore, we introduce an optimization process for this standard deviation to avoid divergence in updating the reconstruction matrix. Numerical simulations verify that our proposed algorithm remarkably enhances the separation performance compared to the conventional one, and accomplishes a super-resolution separation even in noisy situations.

In spectrum sensing, if the primary user (PU) signal and the channel noise both follow Gaussian distribution and neither of their probability distribution functions (PDFs) are known, the traditional approaches based on entropy or Likelihood Ratio Test (LRT) etc., become infeasible. To address this problem, we propose a spectrum sensing method that exploits the similarity of PDFs of two time-adjacent detected data sets with cross entropy, while accounting for achieving the detection performance of LRT which is Neyman-Pearson optimal in detecting the primary user. We show that the detection performance of the proposed method asymptotically approximates that of LRT in detecting the PU. The simulation results confirm our analysis.

In this letter, we derive a probability density function (PDF) for a modulus of product of two complex-valued Gaussian random variables. The PDF is expressed using Modified Bessel Functions, and the probability distribution is named Gaussian Product Modulus Distribution. Some examples of expectation calculation are provided.

An adaptive algorithm to optimize the packet size in wireless mobile networks with Gauss-Markov mobility is presented. The proposed control algorithm conducts adaptive packet size control for mobile terminals that experience relatively fast changing channel conditions, which could be caused by fast mobility or other rapidly changing interference conditions. Due to the fast changing channel conditions, the packet size controller uses short channel history for channel status estimation and takes advantage of a pre-calculated probability density function (PDF) of the distance of the mobile nodes in the estimation process. The packet size is adapted to maximize the communication performance through automatic repeat request (ARQ). The adaptive packet size controlling algorithm is based on an estimation of the channel error rate and the link statistics obtained from the mobility pattern. It was found that the distribution of the link distance among mobile nodes following the Markov-Gauss mobility pattern in a circular communication range well fits the Beta PDF. By adapting the Beta PDF from the mobility pattern, the results show that it is possible to estimate the channel condition more accurately and thereby improve the throughput and utilization performance in rapidly changing wireless mobile networking systems.

This paper studies two types of documents in which an adversary can forge a signature on a chosen document. One type is that a nonce is padded on an input document. The time-stamp protocol is a good example of this type. Another is a structured document (such as PS or PDF) whose contents are described in a body part and information (such as generated time and a generator) are in a meta part. In fact, this paper shows how to forge a time-stamp, a signature on a PDF and an X.509 certificate by the extended forgery attack and numerical examples. Forged signature by the original or the extended attacks is only accepted by the clients whose length check of zero-field is loosely implemented. As a result, we found that the latest versions of Adobe's Acrobat and Acrobat Reader accept the forged time-stamp and the forged signature on a PDF document. Target of this attack is RSASSA-PKCS1-v1_5, which does not have provable security. We also show the expanded attack might forge the signature of RSASSA-PSS, which has provable security, when the length check of zero-field is omitted or loosely implemented.

Multiple-input multiple-output (MIMO) maximum-SNR (max-SNR) system employs the maximum ratio combiner (MRC) at the receiver side and the maximum ratio transmitter (MRT) at the transmitter side. Its performances highly depend on MIMO channel characteristics, which vary according to both the number of antennas and their distribution between the transmitter and receiver sides. By using the decomposition of the ordered Wishart distribution in the uncorrelated Rayleigh case, we derived a closed-form expression of the largest eigenvalue probability density function (PDF). The final result yields to an expression form of the PDF where polynomials are multiplied by exponentials; it is worth underlining that, though this form had been previously observed for given couples of antennas, to date no formally-written closed-form was available in the literature for an arbitrary couple. Then, this new expression permits one to quickly and easily get the well known largest eigenvalue PDF and use it to determine the binary error probability (BEP) of the max-SNR.

We describe a statistical parametric speech synthesis system developed by a joint group from the Nagoya Institute of Technology (Nitech) and the Nara Institute of Science and Technology (NAIST) for the annual open evaluation of text-to-speech synthesis systems named Blizzard Challenge 2006. To improve our 2005 system (Nitech-HTS 2005), we investigated new features such as mel-generalized cepstrum-based line spectral pairs (MGC-LSPs), maximum likelihood linear transform (MLLT), and a full covariance global variance (GV) probability density function (pdf). A combination of mel-cepstral coefficients, MLLT, and full covariance GV pdf scored highest in subjective listening tests, and the 2006 system performed significantly better than the 2005 system. The Blizzard Challenge 2006 evaluations show that Nitech-NAIST-HTS 2006 is competitive even when working with relatively large speech databases.

The supertask approach was proposed by Moir and Ramamthy as a means of supporting non-migratory tasks in Pfair-scheduled systems. In this approach, tasks bound to the same processor are combined into a single server task, called a supertask, which is scheduled as an ordinary Pfair task. When a supertask is scheduled, one of its component tasks is selected for execution. In previous work, Holman et al. showed that component-task deadlines can be guaranteed by inflating each supertask's utilization. In addition, their experimental results showed that the required inflation factors should be small in practice. Consequently, the average inflation produced by their rules is much greater than that actually required by the supertasks. In this paper, we first propose a notion of Transient Behavior Prediction for supertasks, which predicts the latest possible finish time of subtasks that belong to supertasks. On the basis of the notion, we present an efficient schedulability algorithm for Pfair supertasks in which the deadlines of all component tasks can be guaranteed. In addition, we propose a task merging process which combines the unschedulable supertasks with some Pfair tasks; hence, a newly supertask can be scheduled in the system. Finally, we propose the new reweighting functions that can be used when the previous two methods fail. Our reweighting functions produce smaller inflation factor than the previous work does. To demonstrate the efficacy of the supertasking approach, we present the experimental evaluations of our algorithm, which decreases substantially a number of reweights and the size of inflation when there are many supertasks in the Pfair-scheduled systems.

This study was designed to evaluate localized muscular fatigue induced during mouse operation in a VDT task. Ten male undergraduates from 19 to 23 years old participated in the experiment. The subject performed a pointing task with a PC mouse for about 4 hours. The EMG measurements and psychological rating of fatigue were conducted before the experimental task and after each 30-minutes block during the experimental task. The changes in the Mean Power Frequency (MPF) and Percentage Maximum Voluntary Contraction (%MVC)-shift for the constant cumulative probability in the Amplitude Probability Distribution Function (APDF) with time were explored. The correspondence between the index (MPF or APDF) and the subjective rating of localized muscular fatigue was also examined. The performance was nearly constant across all blocks. The psychological rating of fatigue tended to increase with time. The MPF tended to increase with time, although the main effect of block (time) was not statistically significant. The %MVC-shift tended to increase with time. The correspondence with the perceived sensation of localized muscular fatigue was higher when using the %MVC-shift than when using the MPF. Based on the results, the effectiveness of the indexes used for evaluating localized muscular fatigue was discussed. The %MVC-shift obtained from the APDF was found to be a sensitive index of localized muscular fatigue and corresponded well with the subjective rating of localized muscular fatigue.