The blind separation of sources is a recent and important problem in signal processing. Since 1984, it has been studied by many authors whilst many algorithms have been proposed. In this paper, the description of the problem, its assumptions, its currently applications and some algorithms and ideas are discussed.

This paper presents a new adaptive blind separation of sources (BSS) method for linear and non-linear mixtures. The sources are assumed to be statistically independent with non-uniform and symmetrical PDF. The algorithm is based on both simulated annealing and density estimation methods using a neural network. Considering the properties of the vectorial spaces of sources and mixtures, and using some linearization in the mixture space, the new method is derived. Finally, the main characteristics of the method are simplicity and the fast convergence experimentally validated by the separation of many kinds of signals, such as speech or biomedical data.

Since the beginning of the last two decades, many researchers have been involved in the problem of Blind Source Separation (BSS). Whilst hundreds of algorithms have been proposed to solve BSS. These algorithms are well known as Independent Component Analysis (ICA) algorithms. Nowadays, ICA algorithms have been used to deal with various applications and they are using many performance indices. This paper is dedicated to classify the different algorithms according to their applications and performances.

Recent studies on switching fabrics mainly focus on the switching schedule algorithms, which aim at improving the throughput (a key performance metric). However, the delay (another key performance metric) of switching fabrics cannot be well guaranteed. A good switching fabric should be endowed with the properties of high throughput, delay guarantee, low component complexity and high-speed multicast, which are difficult for conventional switching fabrics to achieve. This has fueled great interest in designing a new switching fabric that can support large-scale extension and high-speed multicast. Motivated by this, we reuse the self-routing Boolean concentrator network and embed a model of multicast packet copy separation in front to construct a load-balanced multicast switching fabric (LB-MSF) with delay guarantee. The first phase of LB-MSF is responsible for balancing the incoming traffic into uniform cells while the second phase is in charge of self-routing the cells to their final destinations. In order to improve the throughput, LB-MSF is combined with the merits of erasure codes against packet loss. Experiments and analyses verify that the proposed fabric is able to achieve high-speed multicast switching and suitable for building super large-scale switching fabric in Next Generation Network(NGN) with all the advantages mentioned above. Furthermore, a prototype of the proposed switch is developed on FPGA, and presents excellent performance.

This paper presents a novel and successful optimization algorithm for optimizing Multiple-valued Logic (MVL) functions based on Petri net theory. Mathematical properties and Petri net modeling tools to implement MVL systems are introduced. On the basis of these properties and modeling tools, the optimization algorithm can synthesize, analyze and minimize an arbitrary quaternary logic function of n-input variables. The analysis technique of optimization algorithm is a well-established concept from both theories of MVL and Petri nets, and this can be applied to specify and optimize any MVL Petri net system. In this paper, Petri nets of Galois field have been proposed in order to form a complete system, which can be used to realize and construct VLSI circuit of any MVL function. Based on the Petri nets of Galois field and the proposed algorithm, the quaternary minimum and maximum functions have been analyzed, minimized, and designed. These applications have demonstrated the usefulness of optimization algorithm. Based on Petri net theory, the analysis revealed important information about MVL Petri net modeled systems, where this information has been used to evaluate the modeled system and suggest improvements or changes. For evaluation, advantages of the proposed method over a conventional logic minimization method are presented. Also, we have observed that the MVL Petri nets have the following advantages: Designers can exhibit clearly, simply and systematically any complex MVL Petri net nodel, number of concurrent operations is increased, number of places and transitions that are needed to realize a MVL model is very small, and the interconnection problems can be greatly reduced.

A new circuit design of Josephson ternary δ-gate composed of Josephson junction devices is presented. Mathematical theory for synthesizing, analyzing, and realizing any given function in ternary system using Josephson ternary δ-gate is introduced. The Josephson ternary δ-gate is realized using SQUID technique. Circuit simulation results using J-SPICE demonstrated the feasibility and the reliability operations of Josephson ternary δ-gate with very high performances for both speed and power consumption (max. propagation delay time44 ps and max. power consumption2.6µW). The Josephson ternary δ-gate forms a complete set (completeness) with the ternary constants (1, 0, 1). The number of SQUIDs that are needed to perform the operation of δ-gate is 6. Different design with less than 6 SQUIDs is not possible because it can not perform the operation of δ-gate. The advantages of Josephson ternary δ-gate compared with different Josephson logic circuits are as follows: The δ-gate has the property that a simple realization to any given ternary logic function as the building blocks can be achieved. The δ-gate has simple construction with small number of SQUIDs. The δ-gate can realize a large number of ternary functions with small number of input/output pins. The performances of δ-gate is very high, very low power consumption and ultra high speed switching operation.

Containers offer a lightweight alternative over virtual machines and become a preferable choice for application consolidation in the clouds. However, the sharing of kernel components can violate the I/O performance and isolation in containers. It is widely recognized that file system journaling has terrible performance side effects in containers, especially when consolidating database management systems (DBMSs). The sharing of journaling modules among containers causes performance dependency among them. This dependency violates resource consumption enforced by the resource controller, and degrades I/O performance due to the contention of the journaling module. The operating system developers have been working on novel designs of file systems or new journaling mechanisms to solve the journaling problems. This paper shows that it is possible to overcome journaling problems without re-designing file systems or implementing a new journaling method. A careful configuration of containers in existing file systems can gracefully solve the problems. Our recommended configuration consists of 1) per-container journaling by presenting each container with a virtual block device to have its own journaling module, and 2) accounting journaling I/Os separately for each container. Our experimental results show that our configuration resolves journaling-related problems, improves MySQL performance by 3.4x, and achieves reasonable performance isolation among containers.

If the signal is not Gaussian, then the power spectral density (PSD) approach is insufficient to analyze signals and we resort to estimate the higher order spectra of the signal. However, estimation of the higher order spectra is even more time consuming, for example, the complexity of trispectrum is O(N 4). This problem becomes even more serious when short time Fourier transform (STFT) is computed - computation of the trispectrum is required after every shift of the window. In this paper, a method to recursively compute trispectrum has been presented and it is shown that the computational complexity, for a window size of N, is reduced to be O(N 3) and is the same as the space complexity.

We propose a novel architecture (Switched Access Star: SAS) using an optical switch for access networks and prove its operating principle experimentally. In this architecture, the multiple optical network units (ONUs) in subscriber premises are connected to one optical subscriber unit (OSU) in a central office through an optical switch. SAS can increase the number of accommodated ONUs, the transmission line length, and the capacity per ONU. Moreover, this architecture does not need encryption or ID/passwords. SAS can reduce system cost and yield flexible transmission capacities and realize easy management and maintenance of optical transmission lines.

This paper presents a novel and successful logic synthesis method for optimizing ternary logic functions of any given number of input variables. A new optimization algorithm to synthesize and minimize an arbitrary ternary logic function of n-input variables can always lead this function to optimal or very close to optimal solution, where [n (n1)/2]1 searches are necessary to achieve the optimal solution. Therefore, the complexity number of this algorithm has been greatly reduced from O(3n) into O(n2). The advantages of this synthesis and optimization algorithm are: (1) Very easy logic synthesis method. (2) Algorithm complexity is O(n2). (3) Optimal solution can be obtained in very short time. (4) The method can solve the interconnection problems (interconnection delay) of VLSI and ULSI processors, where very fast and parallel operations can be achieved. A transformation method between operational and polynomial domains of ternary logic functions of n-input variables is also discussed. This transformation method is very effective and simple. Design of the circuits of GF(3) operators, addition and multiplication mod-3, have been proposed, where these circuits are composed of Josephson junction devices. The simulation results of these circuits and examples show the following advantages: very good performances, very low power consumption, and ultra high speed switching operation.

This study proposes a feature-level fusion method that uses finger veins (FVs) and finger dorsal texture (FDT) for personal authentication based on orientation selection (OS). The orientation codes obtained by the filters correspond to different parts of an image (foreground or background) and thus different orientations offer different levels of discrimination performance. We have conducted an orientation component analysis on both FVs and FDT. Based on the analysis, an OS scheme is devised which combines the discriminative orientation features of both modalities. Our experiments demonstrate the effectiveness of the proposed method.

We propose a neighbor pattern coding (NPC) scheme with the aim of exploiting the structural feature fully to improve the performance of finger vein verification. First, one-pixel-wide edge is obtained to represent the direction of the binary vein pattern. Second, based on 8-neighbor pattern analysis, we design a feature-coding strategy to characterize the vein edge. Finally, the edge code flooding operation is defined to characterize all of other vein pixels according to the nearest neighbor principle. Experimental results demonstrate the effectiveness of the proposed method.

Power Spectral Density (PSD) computed by taking the Fourier transform of auto-correlation functions (Wiener-Khintchine Theorem) gives better result, in case of noisy data, as compared to the Periodogram approach in case the signal is Gaussian. However, the computational complexity of Wiener-Khintchine approach is more than that of the Periodogram approach. For the computation of short time Fourier transform (STFT), this problem becomes even more prominent where computation of PSD is required after every shift in the window under analysis. This paper presents a recursive form of PSD to reduce the complexity. If the signal is not Gaussian, the PSD approach is insufficient and we estimate the higher order spectra of the signal. Estimation of higher order spectra is even more time consuming. In this paper, recursive versions for computation of bispectrum has been presented as well. The computational complexity of PSD and bispectrum for a window size of N, are O(N) and O(N2) respectively.

Efficiency and flexibility of collections have a significant impact on the overall performance of applications. The current approaches to implement collections have two main drawbacks: (i) they limit the efficiency of collections and (ii) they have not adequate support for collection composition. So, when the efficiency and flexibility of collections is important, the programmer needs to implement them himself, which leads to the loss of reusability. This article presents neoCollection, a novel approach to encapsulate collections. neoCollection has several distinguishing features: (i) it can be applied on data elements efficiently and flexibly (ii) composition of collections can be made efficiently and flexibly, a feature that does not exist in the current approaches. In order to demonstrate its effectiveness, neoCollection is implemented as an extension to Java and C++.

With the rapid growth on data scale and complexity, single disk failure recovery becomes very important for erasure coded storage systems. In this paper, we propose a new strip-switched deployment method, which utilizes the feature that strips of each stripe of erasure codes could be switched, and uses simulated annealing algorithm to search for the proper strip-deployment on the stack level to balance the read accesses, in order to improve the recovery performance. The analysis and experiments results show that SSDM could effectively improve the single failure recovery performance.

As the demand of data reliability becomes more and more larger, most of today's storage systems adopt erasure codes to assure the data could be reconstructed when suffering from physical device failures. In order to fast recover the lost data from a single failure, recovery optimization methods have attracted a lot of attention in recent years. However, most of the existing optimization methods focus on homogeneous devices, ignoring the fact that the storage devices are usually heterogeneous. In this paper, we propose a new recovery optimization method named HSR (Heterogeneous Storage Recovery) method, which uses both loads and speed rate among physical devices as the optimization target, in order to further improve the recovery performance for heterogeneous devices. The experiment results show that, compared to existing popular recovery optimization methods, HSR method gains much higher recovery speed over heterogeneous storage devices.