Radar Cross Section (RCS) can be obtained from near-field data by using near-field to far-field RCS transformation methods. Phase errors in near-field data cause the degradation of the prediction accuracy. In order to overcome the difficulty, we propose the far-field RCS prediction method from one-dimensional intensity data in near-field. The proposed method is derived by extending the phase retrieval method based on the Gerchberg-Saxton algorithm with the use of the relational expression between near-fields and scattering coefficients. The far-field RCS can be predicted from the intensity data of scattered fields measured at two different ranges. The far-field RCS predicted by the proposed method approximately coincides with the computed one. The proposed method also has significant advantages of simple and efficient algorithm. The proposed method is valuable from a practical point of view.

This paper proposes a closed form solution to L2-sensitivity minimization of second-order state-space digital filters subject to L2-scaling constraints. The proposed approach reduces the constrained optimization problem to an unconstrained optimization problem by appropriate variable transformation. Furthermore, restricting ourselves to the case of second-order state-space digital filters, we can express the L2-sensitivity by a simple linear combination of exponential functions and formulate the L2-sensitivity minimization problem by a simple polynomial equation. As a result, L2-sensitivity is expressed in closed form, and its minimization subject to L2-scaling constraints is achieved without iterative calculations.

In recent years, a horizontal table with a large number of attributes is widely used in OLAP or e-business applications to analyze multidimensional data efficiently. For efficient storing and querying of horizontal tables, recent works have tried to transform a horizontal table to a traditional vertical table. Existing works, however, have the drawback of not considering an optimized PIVOT operation provided (or to be provided) in recent commercial RDBMSs. In this paper we propose a formal approach that exploits the optimized PIVOT operation of commercial RDBMSs for storing and querying of horizontal tables. To achieve this goal, we first provide an overall framework that stores and queries a horizontal table using an equivalent vertical table. Under the proposed framework, we then formally define 1) a method that stores a horizontal table in an equivalent vertical table and 2) a PIVOT operation that converts a stored vertical table to an equivalent horizontal view. Next, we propose a novel method that transforms a user-specified query on horizontal tables to an equivalent PIVOT-included query on vertical tables. In particular, by providing transformation rules for all five elementary operations in relational algebra as theorems, we prove our method is theoretically applicable to commercial RDBMSs. Experimental results show that, compared with the earlier work, our method reduces storage space significantly and also improves average performance by several orders of magnitude. These results indicate that our method provides an excellent framework to maximize performance in handling horizontal tables by exploiting the optimized PIVOT operation in commercial RDBMSs.

Feature transformation in automatic text classification (ATC) can lead to better classification performance. Furthermore dimensionality reduction is important in ATC. Hence, feature transformation and dimensionality reduction are performed to obtain lower computational costs with improved classification performance. However, feature transformation and dimension reduction techniques have been conventionally considered in isolation. In such cases classification performance can be lower than when integrated. Therefore, we propose an integrated feature analysis approach which improves the classification performance at lower dimensionality. Moreover, we propose a multiple feature integration technique which also improves classification effectiveness.

In this paper, a frequency transformation for designing polyphase transfer functions is proposed. A modification to the bilinear LP-LP transformation, which assigns both stopband edges on negative frequency range whereas passband edges are on positive one, results polyphase transfer functions. Design examples show validity of the proposed method.

This paper discusses the behavior of the second-order modes (Hankel singular values) of linear continuous-time systems under variable transformations with positive-real functions. That is, given a transfer function H(s) and its second-order modes, we analyze the second-order modes of transformed systems H(F(s)), where 1/F(s) is an arbitrary positive-real function. We first discuss the case of lossless positive-real transformations, and show that the second-order modes are invariant under any lossless positive-real transformation. We next consider the case of general positive-real transformations, and reveal that the values of the second-order modes are decreased under any general positive-real transformation. We achieve the derivation of these results by describing the controllability/observability Gramians of transformed systems, with the help of the lossless positive-real lemma, the positive-real lemma, and state-space formulation of transformed systems.

This paper discusses the behavior of the second-order modes (Hankel singular values) of linear discrete-time systems under bounded-real transformations, where the transformations are given by arbitrary transfer functions with magnitude bounded by unity. Our main result reveals that the values of the second-order modes are decreased under any of the above-mentioned transformations. This result is the generalization of the theory of Mullis and Roberts, who proved that the second-order modes are invariant under any allpass transformation, i.e. any lossless bounded-real transformation. We derive our main result by describing the controllability/observability Gramians of transformed systems with the help of the discrete-time bounded-real lemma.

This paper discusses the behavior of the second-order modes (Hankel singular values) of linear continuous-time systems under typical frequency transformations, such as lowpass-lowpass, lowpass-highpass, lowpass-bandpass, and lowpass-bandstop transformations. Our main result establishes the fact that the second-order modes are invariant under any of these typical frequency transformations. This means that any transformed system that is generated from a prototype system has the same second-order modes as those of the prototype system. We achieve the derivation of this result by describing the state-space equations and the controllability/observability Gramians of transformed systems.

This paper investigates the use of the affine transformation matrix when employing principal component analysis (PCA) to compress the data of 3D animation models. Satisfactory results were achieved for the common 3D models by using PCA because it can simplify several related variables to a few independent main factors, in addition to making the animation identical to the original by using linear combinations. The selection of the principal component factor (also known as the base) is still a subject for further research. Selecting a large number of bases could improve the precision of the animation and reduce distortion for a large data volume. Hence, a formula is required for base selection. This study develops an automatic PCA selection method, which includes the selection of suitable bases and a PCA separately on the three axes to select the number of suitable bases for each axis. PCA is more suitable for animation models for apparent stationary movement. If the original animation model is integrated with transformation movements such as translation, rotation, and scaling (RTS), the resulting animation model will have a greater distortion in the case of the same base vector with regard to apparent stationary movement. This paper is the first to extract the model movement characteristics using the affine transformation matrix and then to compress 3D animation using PCA. The affine transformation matrix can record the changes in the geometric transformation by using 44 matrices. The transformed model can eliminate the influences of geometric transformations with the animation model normalized to a limited space. Subsequently, by using PCA, the most suitable base vector (variance) can be selected more precisely.

This paper proposes a Mel-Wiener filter to enhance Mel-LPC spectra in the presence of additive noise. The transfer function of the proposed filter is defined by using a first-order all-pass filter instead of unit delay. The filter coefficients are estimated based on minimization of the sum of the square error on the linear frequency scale without applying the bilinear transformation and efficiently implemented in the autocorrelation domain. The proposed filter does not require any time-frequency conversion, which saves a large amount of computational load. The performance of the proposed system is comparable to that of ETSI AFE. The optimum filter order is found to be 3, and thus filtering is computationally inexpensive. The computational cost of the proposed system except VAD is 53% of ETSI AFE.

Due to its importance in engineering applications, the bilinear transformation has been studied in many literature. In this letter two new algorithms are presented to compute transformation matrix for the bilinear s-z transformation.

The completeness (i.e. confluent and terminating) property is an important concept when using a term rewriting system (TRS) as a computational model of functional programming languages. Knuth and Bendix have proposed a procedure known as the KB procedure for generating a complete TRS. A TRS cannot, however, directly handle higher-order functions that are widely used in functional programming languages. In this paper, we propose a higher-order KB procedure that extends the KB procedure to the framework of a simply-typed term rewriting system (STRS) as an extended TRS that can handle higher-order functions. We discuss the application of this higher-order KB procedure to a certification technique called inductionless induction used in program verification, and its application to fusion transformation, a typical kind of program transformation.

A novel pedestrian tracking scheme based on a particle filter is proposed, which adopts a skeleton model of a pedestrian for a state space model and distance transformed images for likelihood computation. The 6-stick skeleton model used in the proposed approach is very distinctive in representing a pedestrian simply but effectively. By the experiment using the real sequences provided by PETS, it is shown that the target pedestrian is tracked adequately by the proposed approach with a simple silhouette extraction method which consists of only background subtraction, even if the tracking target moves so complicatedly and is often so cluttered by other obstacles that the pedestrian can not be tracked by the conventional methods. Moreover, it is demonstrated that the proposed scheme can track the multiple targets in the complex case that their trajectories intersect.

Element value spread of an equal-ripple RC polyphase filter depends heavily on the order of zero assignment. To find the optimum design, we must conduct exhaustive design for all the possible zero assignments. This paper describes two circuit transformations on equal-ripple RC polyphase filters, which preserve their transfer functions, for reducing circuit design efforts. Proposed Method I exchanges (R,C) values to (1/C,1/R) for each stage. This gives a new circuit with different zero assignment for each stage of its original circuit. Method II flips over the original circuit and exchanges the resulting (Ri,Ci) values for (Cn-i+1,Rn-i+1) for each i-th stage. Those circuit transformations can reduce a number of circuit designs down to 1/4 of the straight-forward method. This considerably reduces a burden for exhaustive design for searching the minimum element value spread condition. Some design examples are given to illustrate the proposed methods.

This paper presents a structural approach for synthesizing arbitrary multi-output multi-stage static CMOS circuits at the transistor level, targeting the reduction of transistor counts. To make the problem tractable, the solution space is restricted to the circuit structures which can be obtained by performing algebraic transformations on an arbitrary prime-and-irredundant two-level circuit. The proposed algorithm is guaranteed to find the optimal solution within the solution space. The circuit structures are implicitly enumerated via structural transformations on a single graph structure, then a dynamic-programming based algorithm efficiently finds the minimum solution among them. Experimental results on a benchmark suite targeting standard cell implementations demonstrate the feasibility and effectiveness of the proposed approach. We also demonstrated the efficiency of the proposed algorithm by a numerical analysis on randomly-generated problems.

A unified representation for various kinds of speculations and global scheduling algorithms is presented. After introducing several types of local and global speculations, reviewing our conventional method called conditional vector-based list scheduling, and discussing some of its limitations, we introduce the unique notion of generalized condition vectors (GCVs), which can represent most varieties of speculations and multiple branches as a single vector. The unification of parallel branches and partially unresolved nested conditional branches is discussed. Then, a scheduling algorithm using GCVs is proposed. Experimental results show the effectiveness of the GCV-based scheduling method.

Binary sequences with two-level periodic autocorrelation correspond directly to cyclic (v, k, λ)-designs. When v = 4t-1, k = 2t -1 and λ = t-1, for some positive integer t, the sequence (or design) is called a cyclic Hadamard sequence (or design). For all known examples, v is either a prime number, a product of twin primes, or one less than a power of 2. Except when v = 2k-1, all known examples are based on quadratic residues (using the Legendre symbol when v is prime, and the Jacobi symbol when v = p(p+2) where both p and p+2 are prime); or sextic residues (when v is a prime of the form 4a2 + 27). However, when v = 2k-1, many constructions are now known, including m-sequences (corresponding to Singer difference sets), quadratic and sextic residue sequences (when 2k-1 is prime), GMW sequences and their generalizations (when k is composite), certain term-by-term sums of three and of five m-sequences and more general sums of trace terms, several constructions based on hyper-ovals in finite geometries (found by Segre, by Glynn, and by Maschietti), and the result of performing the Welch-Gong transformation on some of the foregoing.

A novel method is proposed to synthesize dual-band bandpass filters (BPFs) from a prototype lowpass filter. By implementing successive frequency transformations and circuit conversions, a new filter topology is obtained which consists of only admittance inverters and series or shunt resonators, and is thereby easy to be realized by using conventional distributed elements. A microstrip dual-band BPF with central frequencies of 1.8 GHz and 2.4 GHz is designed and fabricated using microstrip lines and stubs. The simulated and measured results show a good agreement and validate thereby the proposed theory.

The Navigational Programming (NavP) methodology is based on the principle of self-migrating computations. It is a truly incremental methodology for developing parallel programs: each step represents a functioning program, and each intermediate program is an improvement over its predecessor. The transformations are mechanical and straightforward to apply. We illustrate our methodology in the context of matrix multiplication, showing how the transformations lead from a sequential program to a fully parallel program. The NavP methodology is conducive to new ways of thinking that lead to ease of programming and high performance. Even though our parallel algorithm was derived using a sequence of mechanical transformations, it displays certain performance advantages over the classical handcrafted Gentleman's Algorithm.

In this paper authorization-limited transformation-free proxy cryptosystems (AL-TFP systems) are studied. It is a modification of the original proxy cryptosystem introduced by Mambo et al.[8] in which a ciphertext transformation by the original decryptor is necessary, and also a modification of the delegated decryption system proposed by Mu et al.[10]. In both systems proposed in [8] and [10], the original decryptors have to trust their proxies completely. The AL-TFP system allows the proxy decryptor to do decryption directly without any ciphertext transformation from the original decryptor, so that it can release the original decryptor more efficiently from a large amount of decrypting operations. Moreover, the original decryptor's privacy can be protected efficiently because the authority of proxy decryptor is limited to his duty and valid period. An active identity-based and a directory-based AL-TFP systems from pairings are proposed. Furthermore, an application of directory-based AL-TFP system to electronic commerce is also described. The securities of our schemes introduced are based on the BDH assumption.