H∞ optimal control is one of the most successful achievements in the post modern control theory. In the H∞ optimal control, we design a controller that minimizes the H∞ norm of a given system. Although the algorithms to solve the problem have already been reported, they focus on numerical systems (systems without any unknown parameters) and, can not be applied for parametric systems (systems with unknown parameters). Given a parametric system, this paper presents an algorithm to compute the optimal H∞ norm of the system achieved by an output feedback controller. The optimal H∞ norm is expressed as , where φ(k) denotes a root of a bivariate polynomial. A numerical example is given to show the effectiveness of the algorithm.

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.

This letter proposes a new algorithm of refining the quantization parameter in H.264 real-time encoding. In the H.264 encoding, the quantization parameter computed according to the quadratic rate model is not accurate in meeting the target bit rate. In order to make the actual encoded bit rate closer to the target bit rate, ρ-domain rate model is introduced in our proposed quantization parameter refinement algorithm. Simulation results show that the proposed algorithm achieves obvious gain in PSNR and has stabler encoded bit rate compared to Jiang's algorithm.

UHF radio frequency identification (RFID) has gathered significant interest in the field of long-distance automatic identification applications. Since UHF RFID shares the frequency band with other RFID and/or other wireless systems, it is important to determine how much interference can be applied without causing a significant degradation of anti-collision speed. In this paper, the permissible link quality for RFID anti-collision in a practical environment is discussed by considering an erroneous communication link, taking into account of bit encoding and the type of interference. We approach the quantification of permissible link quality experimentally along with protocol simulations and the mathematical analyses. An international standard protocol, employing frame slotted ALOHA, was used as the air protocol. For these investigations, the present authors developed a protocol simulator. The simulation results were compared with analytical values based on Poisson distribution. The investigation in the return (tag to reader) link, and the forward (reader to tag) link, were analyzed separately. As result of the protocol simulation, it is generally important to secure the Pulse Error Rate 10-4 or better in both return and forward links for the anti-collision of 64 or less tags. The quality of the return link may be relaxed when the application does not require fast anti-collision. The degradation of the forward link, on the other hand, may entail loss of important commands, resulting in extremely slow anti-collision. It is measured experimentally that the required link quality can be relaxed by up to 10 dB in the return links and by 5 dB in the forward link when the primary source of interference originates in the interfering readers.

Facial skin detection is an important step in facial surgical planning like as many other applications. There are many problems in facial skin detection. One of them is that the image features can be severely corrupted due to illumination, noise, and occlusion, where, shadows can cause numerous strong edges. Hence, in this paper, we present an automatic Expectation-Maximization (EM) algorithm for facial skin color segmentation that uses knowledge of chromatic space and varying illumination conditions to correct and segment frontal and lateral facial color images, simultaneously. The proposed EM algorithm leads to a method that allows for more robust and accurate segmentation of facial images. The initialization of the model parameters is very important in convergence of algorithm. For this purpose, we use a method for robust parameter estimation of Gaussian mixture components. Also, we use an additional class, which includes all pixels not modeled explicitly by Gaussian with small variance, by a uniform probability density, and amending the EM algorithm appropriately, in order to obtain significantly better results. Experimental results on facial color images show that accurate estimates of the Gaussian mixture parameters are computed. Also, other results on images presenting a wide range of variations in lighting conditions, demonstrate the efficiency of the proposed color skin segmentation algorithm compared to conventional EM algorithm.

Quantifying user satisfaction is essential, because the results can help service providers deliver better services. In this work, we propose a generalizable methodology, based on survival analysis, to quantify user satisfaction in terms of session times, i.e., the length of time users stay with an application. Unlike subjective human surveys, our methodology is based solely on passive measurement, which is more cost-efficient and better able to capture subconscious reactions. Furthermore, by using session times, rather than a specific performance indicator, such as the level of distortion of voice signals, the effects of other factors like loudness and sidetone, can also be captured by the developed models. Like survival analysis, our methodology is characterized by low complexity and a simple model-developing process. The feasibility of our methodology is demonstrated through case studies of ShenZhou Online, a commercial MMORPG in Taiwan, and the most prevalent VoIP application in the world, namely Skype. Through the model development process, we can also identify the most significant performance factors and their impacts on user satisfaction and discuss how they can be exploited to improve user experience and optimize resource allocation.

Spoken language understanding (SLU) aims to map a user's speech into a semantic frame. Since most of the previous works use the semantic structures for SLU, we verify that the structure is useful even for noisy input. We apply a structured prediction method to SLU problem and compare it to an unstructured one. In addition, we present a combined method to embed long-distance dependency between entities in a cascaded manner. On air travel data, we show that our approach improves performance over baseline models.

Binary search tree and framed ALOHA algorithms are commonly adopted to solve the anti-collision problem in RFID systems. In this letter, the read efficiency of these two anti-collision algorithms is compared through computer simulations. Simulation results indicate the framed ALOHA algorithm requires less total read time than the binary search tree algorithm. The initial frame length strongly affects the uplink throughput for the framed ALOHA algorithm.

Previous approaches for modeling Intrusion Detection System (IDS) have been on twofold: improving detection model(s) in terms of (i) feature selection of audit data through wrapper and filter methods and (ii) parameters optimization of detection model design, based on classification, clustering algorithms, etc. In this paper, we present three approaches to model IDS in the context of feature selection and parameters optimization: First, we present Fusion of Genetic Algorithm (GA) and Support Vector Machines (SVM) (FuGAS), which employs combinations of GA and SVM through genetic operation and it is capable of building an optimal detection model with only selected important features and optimal parameters value. Second, we present Correlation-based Hybrid Feature Selection (CoHyFS), which utilizes a filter method in conjunction of GA for feature selection in order to reduce long training time. Third, we present Simultaneous Intrinsic Model Identification (SIMI), which adopts Random Forest (RF) and shows better intrusion detection rates and feature selection results, along with no additional computational overheads. We show the experimental results and analysis of three approaches on KDD 1999 intrusion detection datasets.

Random variations in Id-Vg characteristics of MOS transistors in an LSI chip are shown to be concisely characterized by using only 3 transistor parameters (Vth, β0, vSAT) in the MOS level 3 SPICE model. Statistical analyses of the transistor parameters show that not only the threshold voltage variation, ΔVth, but also the current factor variation, Δβ0, independently induces Id-variation, and that Δβ0 is negatively correlated with the saturation velocity variation, ΔvSAT. Using these results, we have proposed a simple method that effectively takes the correlation between parameters into consideration when creating statistical model parameters for designing a circuit. Furthermore, we have proposed a sensitivity analysis methodology for estimating the process window of SRAM cell operation taking transistor variability into account. By applying the concise statistical model parameters to the sensitivity analysis, we are able to obtain valid process windows without the large volume of data-processing and long turnaround time associated with the Monte Carlo simulation. The process window was limited not only by ΔVth, but also by Δβ0 which enhanced the failure region in the process window by 20%.

We analyze the energy consumption of the sensor-medium access control (S-MAC) protocol, where contending nodes exist. Because all nodes running the S-MAC within a virtual cluster always behave with a fixed frame length, the behavior should be analyzed based on its frame. Hence, reflecting the frame architecture, we first present an analytic model for the S-MAC behavior with a discrete-time Markov chain, and then we analyze energy consumption under unsaturated conditions.

In ubiquitous networks based on Wireless Local Area Networks (WLANs) with limited individual coverage, mobile nodes will be likely to traverse different WLANs during TCP communication. An effective handover management scheme for achieving seamless and efficient communication throughout the handover operation is therefore crucial. To achieve this, the following three requirements are essential: (i) early initiation of handover, (ii) elimination of communication interruption upon handover, (iii) selection of an optimal WLAN. The handover scheme proposed in this study employs frame retransmission over WLAN as an indicator of link degradation, and a handover manager (HM) on the transport layer obtains the number of frame retransmissions on the MAC layer using a cross-layer architecture in order to achieve (i) and (iii). Then, it also employs multi-homing in order to achieve (ii). Simulations demonstrate that the proposed scheme can satisfy all of the three requirements and is capable of maintaining TCP performance throughout the handover operation.

Motion-compensated frame interpolation (MCFI) is widely used to smoothly display low frame rate video sequences by synthesizing and inserting new frames between existing frames. The temporal shift interpolation technique (TSIT) is popular for frame interpolation of video sequences that are encoded by a block-based video coding standard such as MPEG-4 or H.264/AVC. TSIT assumes the existence of a motion vector (MV) and may not result in high-quality interpolation for intra-mode blocks that do not have MVs. This paper proposes a new frame interpolation algorithm mainly designed for intra-mode blocks. In order to improve the accuracy of pixel interpolation, the new algorithm proposes sub-pixel interpolation and the reuse of MVs for their refinement. In addition, the new algorithm employs two different interpolation modes for inter-mode blocks and intra-mode blocks, respectively. The use of the two modes reduces ghost artifacts but potentially increases blocking effects between the blocks interpolated by different modes. To reduce blocking effects, the proposed algorithm searches the boundary of an object and interpolates all blocks in the object in the same mode. Simulation results show that the proposed algorithm improves PSNR by an average of 0.71 dB compared with the TSIT with MV refinement and also significantly improves the subjective quality of pictures by reducing ghost artifacts.

This paper proposes a new parameter estimation method for the MIMO-OFDM MAP receiver with spatial-temporal filters. The proposed method employs eigenvalue decomposition (EVD) so as to attain precise estimates especially under interference-limited conditions in MIMO-OFDM mobile communications. Recursive EVD is introduced to reduce the computational complexity compared to the nonrecursive EVD. The spatial-temporal prewhitening is placed prior to FFT because this arrangement is superior to that of conventional prewhitening posterior to FFT in accuracy of the parameter estimation. In order to improve tracking capability to fast fading, the proposed scheme applies a decision-directed algorithm to the parameter estimation by using log-likelihood ratios of coded bits. Computer simulations demonstrate that the proposed scheme can track fast fading and reduce the complexity to 18 percents of the conventional one, and that the spatial-temporal filtering prior to FFT outperforms the conventional one posterior to FFT.

This study deals with two linear precoders: the maximization of the minimum Euclidean distance between received symbol-vectors, called here max-dmin, and the maximization of the post-processing signal-to-noise ratio termed max-SNR or beamforming. Both have been designed for reliable MIMO transmissions operating over uncorrelated Rayleigh fading channels. Here, we will explain why performances in terms of bit error rates show a significant enhancement of the max-dmin over the max-SNR whenever the number of antennas is increased. Then, from theoretical developments, we will demonstrate that, like the max-SNR precoder, the max-dmin precoder achieves the maximum diversity order, which is warrant of reliable transmissions. The current theoretical knowledge will be applied to the case-study of a system with two transmit- or two receive-antennas to calculate the probability density functions of two channel parameters directly linked to precoder performances for uncorrelated Rayleigh fading channels. At last, this calculation will allow us to quickly get the BER of the max-dmin precoder further to the derivation of a tight semi-theoretical approximation.

Realistic representations using extremely high quality images are becoming increasingly popular. For example, digital cinemas can now display moving pictures composed of high-resolution digital images. Although these applications focus on increasing the spatial resolution only, higher frame-rates are being considered to achieve more realistic representations. Since increasing the frame-rate increases the total amount of information, efficient coding methods are required. However, its statistical properties are not clarified. This paper establishes for high frame-rate video a mathematical model of the relationship between frame-rate and bit-rate. A coding experiment confirms the validity of the mathematical model.

This paper proposes a self-test method of coarse grain dynamically reconfigurable processors (DRPs) without hardware overhead. In the method, processor elements (PEs) compose a test frame, which consists of test pattern generators (TPGs), processor elements under test (PEUTs) and response analyzers (RAs), while testing themselves one another by changing test frames appropriately. We design several test frames with different structures, and discuss the relationship of the structures to the numbers of contexts and test frames for testing all the functions of PEs. A case study shows that there exists an optimal test frame which minimizes the test application time under a constraint.

This letter presents a novel frame splitting scheme for an error-robust audio streaming over packet-switching networks. In our approach to perceptual audio coding, an audio frame is split into several subframes based on the network configuration such that each packet can be decoded independently at the receiver. Through a subjective comparison category rating (CCR) test, it is discovered that our approach enhances the quality of the decoded audio signal under the lossy packet-switching networks environment.

This paper introduces an adaptive low complexity pre-processing filter to improve the coding performance of seriously degraded video sequences that is caused by the additive noise. The additive noise leads to a decrease in coding performance due to the high frequency components. By incorporating local statistics and quantization parameter into filtering process, the spurious noise is significantly attenuated and coding efficiency is improved for given quantization step size. In order to reduce the complexity of the pre-processing filter, the simplified local statistics and quantization parameter are introduced. The simulation results show the capability of the proposed algorithm.

The quality of the Side-information frame (S frame) influences significantly the rate-distortion performance in the Distributed Video Coding (DVC). In this letter, we propose an efficient Side-Information Frame Generator (SIFG). It considers smoothness constraints of both the motion vector field and spatial adjacent pixels. Simulation results show that the proposed techniques provide potential rate-distortion performance advantages. Besides, the fine visual quality of the S frame is obtained.