This paper presents a voice conversion (VC) technique for noisy environments, where parallel exemplars are introduced to encode the source speech signal and synthesize the target speech signal. The parallel exemplars (dictionary) consist of the source exemplars and target exemplars, having the same texts uttered by the source and target speakers. The input source signal is decomposed into the source exemplars, noise exemplars and their weights (activities). Then, by using the weights of the source exemplars, the converted signal is constructed from the target exemplars. We carried out speaker conversion tasks using clean speech data and noise-added speech data. The effectiveness of this method was confirmed by comparing its effectiveness with that of a conventional Gaussian Mixture Model (GMM)-based method.

MIMO transmission technologies have become an essential component of cellular systems such as Long Term Evolution (LTE) and LTE-Advanced. Recently, evaluating the communication performance of mobile users in cellular MIMO systems has become an urgent requirement. In this paper, we propose dynamic MIMO channel modeling for the urban environment. Our proposal is based on Geometry-based Stochastic Channel Modeling (GSCM). The cluster parameters such as the local scatterer locations around the measurement course are estimated by applying the particle filtering to measured data. We carried out radio propagation measurements in an urban environment at 3.35GHz band, and generated the dynamic channel from the measured data. The experiments showed that both the spreads and auto-correlation of Time of Arrival (ToA), Angle of Arrival (AoA) and Angle of Departure (AoD) were reconstructed within the acceptable error range in our dynamic channel model.

Multiple access relay systems with network coding provide spatial diversity with fewer transmissions. However, errors generated at the relay can propagate to the destination and the system performance can be severely degraded. Although many techniques have been proposed to resolve the error propagation, these techniques require some special operations at the relay or complicated reception schemes at the destination unless the global channel state information is available at the destination. This paper proposes a simple cooperative demodulation scheme for multiple access relay systems with network coding assuming that the relay simply forwards the decoded data and the destination has only the local channel state information.

Histogram sequences represent high-dimensional time-series converted from images by space filling curves (SFCs). To overcome the high-dimensionality nature of histogram sequences (e.g., 106 dimensions for a 1024×1024 image), we often use lower-dimensional transformations, but the tightness of their lower-bounds is highly affected by the types of SFCs. In this paper we attack a challenging problem of evaluating which SFC shows the better performance when we apply the lower-dimensional transformation to histogram sequences. For this, we first present a concept of spatial locality and propose spatial locality preservation metric (SLPM in short). We then evaluate five well-known SFCs from the perspective of SLPM and verify that the evaluation result concurs with the actual transformation performance. Finally, we empirically validate the accuracy of SLPM by providing that the Hilbert-order with the highest SLPM also shows the best performance in k-NN (k-nearest neighbors) search.

In order to employ Multiple-Input-Multiple-Output (MIMO) techniques, multiple antenna branches are necessary and as a consequence the installation space requirements are increased. Since the installation space is limited, much attention is now focused on utilizing polarization characteristics in MIMO configurations to relax the requirements. This is called Orthogonal Polarization-MIMO in this paper. To evaluate accurately the performance of Orthogonal Polarization-MIMO, a channel model that can handle the polarization dispersion characteristics of propagation paths is essential. Up to now, the spatial-temporal dispersion characteristics of paths have been investigated in detail. However, there are only a few reports on the polarization dispersion characteristics. In this paper, we propose a new power profile for the rotational polarized angle as an evaluation model for polarization dispersion, and clarify the analyzed power profile based on measurement data in an urban macrocell environment.

The optimal design of an extrapolated impulse response (EIR) filter (in the mini-max sense) is a non-linear programming problem. In this paper, the optimal design of the EIR filter by the semi-infinite programming (SIP) is investigated and an iterative technique for optimally designing the EIR filter is proposed. The simulation experiment validates the effectiveness of the SIP technique and the proposed iterative technique in the optimal design of the EIR filter.

We consider uplink multi-carrier code-division multiple access (MC-CDMA) systems in a multi-cell environment. It is assumed that all intra-cell users employ Alamouti's simple space-time block coding (STBC), which is known to the base station receiver, but the receiver has no information on whether inter-cell users employ STBC or not. In this case we propose a blind adaptive minimum output energy (MOE) receiver for uplink STBC MC-CDMA, which is designed to perfectly remove the interference from intra-cell users by using the spreading sequence information on all intra-cell users and to reduce the interference from inter-cell users by minimizing the constrained output energy. Analysis and simulation results show that the proposed adaptive receiver has a faster convergence rate and higher steady-state signal-to-interference plus noise ratio (SINR) than a conventional scheme in which only the spreading code information of the desired user is utilized.

In the recently developed Flexible Wireless System (FWS), the same platform needs to deal with different wireless systems. This increases nonlinear distortion in its wideband power amplifier (PA) because the PA needs to concurrently amplify multi-band signals. By taking higher harmonics as well as inter- and cross-modulation distortion into consideration, we have developed a method to analytically evaluate the adjacent channel leakage power ratio (ACPR) and error vector magnitude (EVM) on the basis of the PA's nonlinear characteristics. We devise a novel method for modeling the PA amplifying dual-band signals. The method makes it possible to model it merely by performing a one-tone test, making use of the Volterra series expansion and the general Wiener model. We then use the Mehler formula to derive the closed-form expressions of the PA's output power spectral density (PSD), ACPR, and EVM. The derivations are based on the assumption that the transmitted signals are complex Gaussian distributed in orthogonal frequency division multiplexing (OFDM) transmission systems. We validate the method by comparing measurement and simulation results and confirm it can appropriately predict the ACPR and EVM performance of the nonlinear PA output with OFDM inputs. In short, the method enables correct modeling of a wideband PA that amplifies dual-band signals merely by conducting a one-tone test.

A directional lapped orthogonal transform (DirLOT) is an orthonormal transform of which basis is allowed to be anisotropic with the symmetric, real-valued and compact-support property. Due to its directional property, DirLOT is superior to the existing separable transforms such as DCT and DWT in expressing diagonal edges and textures. The goal of this paper is to enhance the ability of DirLOT further. To achieve this goal, we propose a novel image restoration technique using multiple DirLOTs. This paper generalizes an image denoising technique in [1], and expands the application of multiple DirLOTs by introducing linear degradation operator P. The idea is to use multiple DirLOTs to construct a redundant dictionary. More precisely, the redundant dictionary is constructed as a union of symmetric orthonormal discrete wavelet transforms generated by DirLOTs. To select atoms fitting a target image from the dictionary, we formulate an image restoration problem as an l1-regularized least square problem, which can efficiently be solved by the iterative-shrinkage/thresholding algorithm (ISTA). The proposed technique is beneficial in expressing multiple directions of edges/textures. Simulation results show that the proposed technique significantly outperforms the non-subsampled Haar wavelet transform for deblurring, super-resolution, and inpainting.

In this paper, we point out that Yoon et al.'s gateway-oriented password-based authenticated key exchange (GPAKE) protocol is inefficiently and incorrectly designed to overcome the undetectable on-line dictionary attack. To remedy these problems, we propose a new GPAKE protocol and prove its security in the random oracle model. Performance analysis demonstrates that our protocol is more secure and efficient than previous protocols.

We address the problem of processing graph pattern matching queries over a massive set of data graphs in this letter. As the number of data graphs is growing rapidly, it is often hard to process such queries with serial algorithms in a timely manner. We propose a distributed graph querying algorithm, which employs feature-based comparison and a filter-and-verify scheme working on the MapReduce framework. Moreover, we devise an efficient scheme that adaptively tunes a proper feature size at runtime by sampling data graphs. With various experiments, we show that the proposed method outperforms conventional algorithms in terms of scalability and efficiency.

This paper presents a new adaptive peak-to-average power ratio (PAPR) reduction method based on clipping and filtering (CF) for precoded orthogonal frequency division multiplexing (OFDM)-multiple-input multiple-output (MIMO) transmission. While the conventional CF method adds roughly the same interference power to each of the transmission streams, the proposed method suppresses the addition of interference power to the streams with good channel conditions. Since the sum capacity is dominated by the capacity of the streams under good channel conditions and the interference caused by the PAPR reduction process severely degrades the achievable capacity for these streams, the proposed method significantly improves the achievable sum capacity compared to the conventional CF method for a given PAPR. Simulation results show the capacity gain by using the proposed method compared to the conventional method.

A CAM-based matching system for fast exact pattern matching is implemented on a hardware system with FPGA and ASIC. The system has a simple structure, and does not employ any Central Processor Unit (CPU) as well as complicated computations. We take advantage of Content Addressable Memory (CAM) which has an ability of parallel multi-match mode for designing the system. The system is applied to fast pattern matching with various required search patterns without using search principles. In this paper, the authors present a CAM-based system for fast exact pattern matching on 2-D data.

Many applications of wireless sensor networks (WSNs) require secure communication. The tree-based key management scheme, which is a symmetric key scheme, provides backward and forward secrecy. The sensor nodes in the communication group share a secret key for encrypting messages. When the sensor nodes are added to or evicted from the group, the group key has to be updated by sending rekeying messages. In this paper, we propose a method of key tree structure (KTS) generation by considering the addition and eviction ratio of sensor nodes to reduce the number of rekeying messages, which is influenced by the structure of the tree. For this, we define an extension of an existing tree structure such as a binary or ternary tree and generate KTS using an A* algorithm. To reduce the energy consumed by the message transmission, we also exploit genetic algorithm (GA) to build a secure communication group by considering the KTS. In the paper, we show the effectiveness of the proposed method compared with the existing structure via the simulation in terms of memory usage, the number of rekeying messages and energy consumption.

A compact DC-DC convertor is proposed and fabricated by LTCC technology. Multilayer packaging structure is utilized for size reduction. Measured results are provided to show good performance and validate proposed structure. With the inductor embedded into ferrite substrate, the convertor exhibits advantages of both miniature size and high reliability compared with conventional ones.

We present an acoustic model adaptation method where the transformation matrix for a new speaker is given by the product of bases and a weight matrix. The bases are built from the parallel factor analysis 2 (PARAFAC2) of training speakers' transformation matrices. We perform continuous speech recognition experiments using the WSJ0 corpus.

In this paper, we propose a novel layered scalable- multiple description coding (LS-MDC) which offers the benefits of both scalable video coding and multiple description coding for robust video transmission over packet lossy networks. In the proposed LS-MDC method, multiple descriptions including base layer, enhancement layers, and their corresponding FEC parity data are allocated into two network paths of a path diversity system. Unlike the conventional approaches, the source base/enhancement data and their own parities in the proposed method are not transmitted together but are transferred over different paths. Therefore, the effect of burst packet losses can be effectively reduced for the descriptions. Furthermore, in order to minimize the overall distortion for the LS-MDC system and exploit the benefits of path diversity, we also propose an optimal rate allocation scheme that can adaptively control the transmission rate as well as the channel coding rate for media senders. Experiments show that the proposed method provides much better peak signal-to-noise ratio (PSNR) than conventional MDC techniques.

In recent years, the growing density and complexity of VLSIs have led to an increase in the numbers of test patterns and fault models. Test patterns used in VLSI testing are required to provide high quality and low cost. Don't care (X) identification techniques and X-filling techniques are methods to satisfy these requirements. However, conventional X-identification techniques are less effective for application-specific fields such as test compaction because the X-bits concentrate on particular primary inputs and pseudo primary inputs. In this paper, we propose a don't care identification method for test compaction. The experimental results for ITC'99 and ISCAS'89 benchmark circuits show that a given test set can be efficiently compacted by the proposed method.

We propose a fault diagnosis and reconfiguration method based on the Pair and Swap scheme to improve the reliability and the MTTF (Mean Time To Failure) of network-on-chip based multiple processor systems where each processor core has its private memory. In the proposed scheme, two identical copies of a given task are executed on a pair of processor cores and the results are compared repeatedly in order to detect processor faults. If a fault is detected by mismatches, the fault is identified and isolated using a TMR (Triple Module Redundancy) and the system is reconfigured by the redundant processor cores. We propose that each task is quadruplicated and statically assigned to private memories so that each memory has only two different tasks. We evaluate the reliability of the proposed quadruplicated task allocation scheme in the viewpoint of MTTF. As a result, the MTTF of the proposed scheme is over 4.3 times longer than that of the duplicated task allocation scheme.

The conventional hybrid STBC schemes can achieve less BER performance for STBC detection schemes than conventional STBC schemes since SM symbols interfere with STBC symbols. Therefore, this letter proposes the improved scheme for hybrid STBC systems. STBC and SM schemes are combined for the hybrid space-time block code system. Our approach effectively obtains both diversity gain and spectral efficiency gain. The proposed scheme offers improved BER performance since it uses iterative detection. Moreover, it increases the data rate effectively with a little performance loss.