This letter presents a new algorithm for improving the Signal to Noise Ratio (SNR) of complex sinusoidal signals contaminated by additive Gaussian noises using sum of Higher-Order Statistics (HOS). We conduct some computer simulations to show that the proposed algorithm can improve the SNR more than 7 dB compared with the conventional coherent integration when the SNR of the input signal is -10 dB.

Computational expensiveness of the training techniques, due to the extensiveness of the data set, is among the most important factors in machine learning and neural networks. Oversized data set may cause rank-deficiencies of Jacobean matrix which plays essential role in training techniques. Then the training becomes not only computationally expensive but also ineffective. In [1] the authors introduced the theoretical grounds for dynamic sample selection having a potential of eliminating rank-deficiencies. This study addresses the implementation issues of the dynamic sample selection based on the theoretical material presented in [1]. The authors propose a sample selection algorithm implementable into an arbitrary optimization technique. An ability of the algorithm to select a proper set of samples at each iteration of the training has been observed to be very beneficial as indicated by several experiments. Recently proposed approaches to sample selection work reasonably well if pattern-weight ratio is close to 1. Small improvements can be detected also at the values of the pattern-weight ratio equal to 2 or 3. The dynamic sample selection approach, presented in this article, can increase the convergence speed of first order optimization techniques, used for training MLP networks, even at the value of the pattern-weight ratio (E-FP) as high as 15 and possibly even more.

In this work, we give a true concurrency semantics for FIFO-nets, that are Petri nets in which places behave as queues, tokens take values in a finite alphabet and the firing of a transition depends on sequences on the alphabet. We introduce fn-processes to represent the concurrent behavior of a FIFO-net N during a sequence of transition firings. Fn-processes are modeled by a mapping from a simple FIFO-net without queue sharing and cycles, named FIFO-occurrence net, to N. Moreover, the relation among the firings expressed by the FIFO-occurrence net has been enriched by an ordering relation among the elements of the FIFO-occurrence net representing values entered into a same queue of N. We give a way to build fn-processes step by step in correspondance with a sequence of transition firings and the fn-processes operationally built are all those abstractly defined. The FIFO-occurrence nets of fn-processes have some interesting properties; for example, such nets are always discrete and, consequently, there is at least a transition sequence corresponding to each fn-process.

In this paper, we extend the Gnaedig's results on termination of order-sorted rewriting. Gnaedig required a condition for order-sorted signatures, called minimality, for the termination proof. We get rid of this restriction by introducing a transformation from a TRS with an arbitrary order-sorted signature to another TRS with a minimal signature, and proving that this transformation preserves termination.

We propose a Generalized Order Statistic Cell Averaging (GOSCA) CFAR detector. The weighted sums of the order statistics in the leading and lagging reference windows are utilized for the background level estimate. The estimate is obtained by averaging the weighted sums. By changing the weighting values, various CFAR detectors are obtained. The main advantage of the proposed GOSCA CFAR detector over the GOS CFAR detector is to reduce a computational time which is critical factor for the real time operation. We also derive unified formulas of the GOSCA CFAR detector under the noncoherent integration scheme. For Swerling target cases, performances of various CFAR detectors implemented using the GOSCA CFAR detector are derived and compared in homogeneous environment, and in the case of multiple targets and clutter edges situations.

This paper describes a new high resolution algorithm for the two-dimensional (2-D) frequency estimation problem, which, in particular, is noise insensitive in view of the fact that in many practical applications the contaminated noise may not be white noise. For this purpose, the approach is set in the context of higher-order statistics (HOS), which has demonstrated to be an effective approach under a colored noise environment. The algorithm begins with the consideration of the fourth-order moments of the available 2-D data. Two auxiliary matrices, constituted by a novel stacking of the diagonal slice of the computed fourth-order moments, are then introduced and through which the two frequency components can be precisely determined, respectively, via matrix factorizations along with the subspace rotational invariance (SRI) technique. Simulation results are also provided to verify the proposed algorithm.

This paper presents some fundamental properties of multiple-valued logic functions monotonic in a partial-ordering relation which is introduced in the set of truth values and does not necessarily have the greatest or least element. Two kinds of necessary and sufficient conditions for monotonic p-valued functions are given with the proofs. Their logic formulas using unary operators defined in the partial-ordering relation and a simplification method for those logic formulas are also given. These results include as their special cases our former results for p-valued functions monotonic in the ambiguity relation which is a partial-ordering relation with the greatest element.

This paper suggests a novel analytical model to predict average issue rate of both in-order and out-of-order issue policies. Most of previous works have employed only simulation methods to measure the instruction-level parallelism for performance. However these methods cannot disclose the cause of the performance bottle-neck. In this paper, the proposed model takes into account such factors as issue policy, instruction-level parallelism, branch probability, the accuracy of branch prediction, instruction window size, and the number of pipeline units to estimate the issue rate more accurately. To prove the correctness of the model, extensive simulations were performed with Intel 80386/80387 instruction traces. Simulation results showed that the proposed model can estimate the issue rate accurately within 3-10% differences. The analytical model and simulations show that the out-of-order issue can improve the superscalar performance by 70-206% compared to the in-order issue. The model employs parameters to characterize the behavior of programs and the structure of superscalar that cause performance bottle-neck. Thus, it can disclose the cause of the disproportion in performance and reduce the burden of excess simulations that should be performed whenever a new processor is designed.

In this paper, we propose dynamic cepstral representations to effectively capture the temporal information of cepstral coefficients. The number of speech frames for the regression analysis to extract a dynamic cepstral coefficient is inversely proportional to the cepstral order since the cepstral coefficients of higher orders are more fluctuating than those of lower orders. By exploiting the relationship between the window length for extracting a dynamic cepstral coefficient and the statistical variance of the cepstral coefficient, we propose three kinds of windowing methods in this work: an utterance-specific variance-ratio windowing method, a statistical variance-ratio windowing method, and an inverse-lifter windowing method. Intra-speaker, inter-speaker, and speaker-independent recognition tests on 100 phonetically balanced words are carried out to evaluate the performance of the proposed order-dependent windowing methods.

In many applications, information retrieval is a very important research field. In several key strategies, the binary trie is famous as a fast access method able to retrieve keys in order. Especially, a Patricia trie gives the shallowest trie by eliminating all nodes which have only one arc, and it requires the smallest storage among the other trie structures. If trie structures are implemented, however, the greater the number of the registered keys, the larger storage is required. In order to solve this problem, Jonge et al. proposed a method to change the normal binary trie into a compact bit stream. This paper proposes the improved trie representation for the Patricia trie, as well as the methods for searching and inserting the key on it. The theoretical and experimental results, using 50,000 Japanese nouns and 50,000 English words, show that this method generates 25-39 percent shorter bit streams than the traditional method. This method, thus, enables us to provide more compact storage and faster access than the traditional method.

Unfolding originally introduced by McMillan is gaining ground as a partial-order based method for the verification of concurrent systems without state space explosion. However, it can be exposed to redundancy which may increase its size exponentially. So far, there have been trials to reduce such redundancy resulting from conflicts by improving McMillan's cut-off criterion. In this paper, we show that concurrency is also another cause of redundancy in unfolding, and present an algorithm to reduce such redundancy in live, bounded and reversible Petri nets which is independent of any cut-off algorithm.

In [1] a generalized concatenated code was used to construct the t-fold unidirectional b-bit-byte error-correcting/d(dt)-fold unidirectional b-bit-byte error-detecting (t-UbEC/d(t)-UbED) codes. The concatenated code is to choose an inner code satisfying some disjoint sets and each set is a binary b-tuples unordered code. However, [1] gave five methods including trial and error to construct the optimal inner codes. Here, we present a systematic method for constructing the inner codes. It is shown that we can improve the coding efficiency for t-UbEC/d(t)-UbED) codes in some cases by using our inner codes.

Though causal order of message delivery simplifies the design and development of distributed applications, the overhead of enforcing it is not negligible. We claim that a causal order algorithm which does not send any redundant information is efficient in the sense of communication overhead. We characterize and classify the redundant information into four categories: information regarding just delivered, already delivered, just replaced, and already replaced messages. We propose an efficient causal multicast algorithm which prevents propagation of these redundant information. Our algorithm sends less amount of control information needed to ensure causal order than other existing algorithms and can also be applied to systems whose communication channels are not FIFO. Since our algorithm's communication overhead increases relatively slowly as the number of processes increases, it shows good scalability feature. The potential of our algorithm is shown by simulation study.

A suggestion for creating an excitable/oscillatory field with solid-state material is proposed. In essence, the idea is to make a spatial array of "mesoscopic particles" with the characteristics of a first-order phase transition. A theoretical computation shows that an auto-wave, or excitable wave, is generated in such an excitable field. A simple example of using this system as a diode in information flow is given.

Some kind of practical problems such as security verification of cryptographic protocols can be described as a problem to accomplish a given purpose by using limited operations and limited materials only. To model such problems in a natural way, unification problems under constrained substitutions have been proposed. This paper is a collection of results on the decidability and the computational complexity of a syntactic unification problem under constrained substitutions. A number of decidable, undecidable, tractable and intractable results of the problem are presented. Since a unification problem under constrained substitutions can be regarded as an order-sorted unification problem with term declarations such that the number of sorts is only one, the results presented in this paper also indicate how the intractability of order-sorted unification problems is reduced by restecting the number of sorts to one.

A new numerical technique, termed the method of matrix-order reduction (MMOR), is developed for handling electromagnetic problems in this paper, in which the matrix equation resulted from a method-of-moments analysis is converted either to an eigenvalue equation or to another matrix equation with the matrix order in both cases being much reduced, and also, the accuracy of solution obtained by solving either of above equations is improved by means of a newly proposed generalized Jacobian iteration. As a result, this technique enjoys the advantages of less computational expenses and a relatively good solution accuracy as well. To testify this new technique, a number of wire antennas are examined and the calculated results are compared with those obtained by using the method of moments.

This paper proposes a new method for recovering the original signals from their linear mixtures observed by the same number of sensors. It is performed by identifying the linear transform from the sources to the sensors, only using the sensor signals. The only assumption of the source signals is basically the fact that they are statistically mutually independent. In order to perform the 'blind' identification, some time-correlational information in the observed signals are utilized. The most important feature of the method is that the full information of available time-correlation data (second-order statistics) is evaluated, as opposed to the conventional methods. To this end, an information-theoretic cost function is introduced, and the unknown linear transform is found by minimizing it. The propsed method gives a more stable solution than the conventional methods.

Ordered Binary Decision Diagrams (OBDDs) are graph-based representations of Boolean functions which are widely used because of their good properties. In this paper, we introduce nondeterministic OBDDs (NOBDDs) and their restricted forms, and evaluate their expressive power. In some applications of OBDDs, canonicity, which is one of the good properties of OBDDs, is not necessary. In such cases, we can reduce the required amount of storage by using OBDDs in some non-canonical form. A class of NOBDDs can be used as a non-canonical form of OBDDs. In this paper, we focus on two particular methods which can be regarded as using restricted forms of NOBDDs. Our aim is to show how the size of OBDDs can be reduced in such forms from theoretical point of view. Firstly, we consider a method to solve satisfiability problem of combinational circuits using the structure of circuits as a key to reduce the NOBDD size. We show that the NOBDD size is related to the cutwidth of circuits. Secondly, we analyze methods that use OBDDs to represent Boolean functions as sets of product terms. We show that the class of functions treated feasibly in this representation strictly contains that in OBDDs and contained by that in NOBDDs.

The currying of term rewriting systems (TRSs) is a transformation of TRSs from a functional form to an applicative form. We have already introduced an order-sorted version of currying and proved that the compatibility and confluence of order-sorted TRSs were preserved by currying. In this paper, we focus on a key property of TRSs, completeness. We first show some proofs omitted in Ref. [3]. Then, we prove that the SN (strongly normalizing) property, which corresponds to termination of a program, is preserved by currying. Finally, we prove that the completeness of compatible order-sorted TRSs is preserved by currying.

In this paper, we propose a clustering based linear ordering algorithm which consists of global ordering and local ordering. In the global ordering, the algorithm forms clusters from n given vertices and orders the clusters. In the local ordering, the elements in each cluster are linearly ordered. The linear order, thus produced, is used to obtain optimal κ-way partitioning based on scaled cost objective function. When the number of cluster is one, the proposed algorithm is exactly the same as MELO [2]. But the proposed algorithm has more global partitioning information than MELO by clustering. Experiment with 11 benchmark circuits for κ-way (2 κ 10) partitioning shows that the proposed algorithm yields an average of 10.6% improvement over MELO [2] for the κ-way scaled cost partitioning.