Author

# Shuichi Itoh

Bio: Shuichi Itoh is an academic researcher from University of Electro-Communications. The author has contributed to research in topic(s): Wavelet & Wavelet transform. The author has an hindex of 9, co-authored 28 publication(s) receiving 497 citation(s).

##### Papers

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TL;DR: A new electrocardiogram compression method based on orthonormal wavelet transform and an adaptive quantization strategy, by which a predetermined percent root mean square difference (PRD) can be guaranteed with high compression ratio and low implementation complexity are presented.

Abstract: This paper presents a new electrocardiogram (ECG) compression method based on orthonormal wavelet transform and an adaptive quantization strategy, by which a predetermined percent root mean square difference (PRD) can be guaranteed with high compression ratio and low implementation complexity.

134 citations

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29 Jun 1997TL;DR: An algorithm is presented which can relax the upper bound for sampling in some wavelet subspaces by using scaling functions and which can estimate a proper upper bound of sup/sub /spl kappa//|/spl delta//sub / spl kappa| such that the irregularly sampled signals can be recovered.

Abstract: From the Paley-Wiener 1/4-theorem, the finite energy signal f(t) can be reconstructed from its irregularly sampled values f(k+/spl delta//sub /spl kappa//) if f(t) is band-limited and sup/sub /spl kappa//|/spl delta//sub /spl kappa//|<1/4. We consider the signals in wavelet subspaces and wish to recover the signals from its irregular samples by using scaling functions. Then the method of estimating the upper bound of sup/sub /spl kappa//|/spl delta//sub /spl kappa//| such that the irregularly sampled signals can be recovered is very important. Following the work done by Liu and Walter (see J. Fourier Anal. Appl., vol.2, no.2, p.181-9, 1995), we present an algorithm which can estimate a proper upper bound of sup/sub /spl kappa//|/spl delta//sub /spl kappa//|. Compared to Paley-Wiener 1/4-theorem, this theorem can relax the upper bound for sampling in some wavelet subspaces.

83 citations

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TL;DR: A necessary and sufficient condition for sampling in the general framework of shift invariant spaces is derived and an improved estimate for the perturbation is derived for theperturbation of regular sampling in shift invariants spaces.

Abstract: A necessary and sufficient condition for sampling in the general framework of shift invariant spaces is derived. Then this result is applied, respectively, to the regular sampling and the perturbation of regular sampling in shift invariant spaces. A simple necessary and sufficient condition for regular sampling in shift invariant spaces is attained. Furthermore, an improved estimate for the perturbation is derived for the perturbation of regular sampling in shift invariant spaces. The derived estimate is easy to calculate, and shown to be optimal in some shift invariant spaces. The algorithm to calculate the reconstruction frame is also presented.

72 citations

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48 citations

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TL;DR: An efficient protocol and associate algorithm for group key management in secure multicast based on a hierarchy approach in which the group is logically divided into subgroups and the inverse value of the leaving member is sent to the subgroups when a member leaves.

Abstract: This paper proposes an efficient protocol and associate algorithm for group key management in secure multicast. This protocol is based on a hierarchy approach in which the group is logically divided into subgroups. The group key is organized using member secrets assigned to each member and server secrets assigned to each subgroup, and the inverse value of the member secrets are also used to manage the group key when a member leaves. In this case, each member in a single subgroup needs to store the inverse values of the other members in that subgroup with the exception of its own. When a member joins the group, after updating the previous group key in the server, the new key is sent to all existing group members, and the inverse value of the new member is sent to subgroup members (where there is a join), by exploiting IP multicast. Most importantly, the server just sends the inverse value of the leaving member to the subgroups when a member leaves. Then, the group key is updated by each remaining member in the subgroups by using that inverse value. Consequently, the benefits are two-fold. First, only one key needs to be generated by the server at each event. Second, not only the computational overhead is reduced but also new key information can be multicast to all members simultaneously. This paper describes the details of our novel protocol and the related algorithm.

37 citations

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01 Apr 2000TL;DR: The standard sampling paradigm is extended for a presentation of functions in the more general class of "shift-in-variant" function spaces, including splines and wavelets, and variations of sampling that can be understood from the same unifying perspective are reviewed.

Abstract: This paper presents an account of the current state of sampling, 50 years after Shannon's formulation of the sampling theorem. The emphasis is on regular sampling, where the grid is uniform. This topic has benefitted from a strong research revival during the past few years, thanks in part to the mathematical connections that were made with wavelet theory. To introduce the reader to the modern, Hilbert-space formulation, we reinterpret Shannon's sampling procedure as an orthogonal projection onto the subspace of band-limited functions. We then extend the standard sampling paradigm for a presentation of functions in the more general class of "shift-in-variant" function spaces, including splines and wavelets. Practically, this allows for simpler-and possibly more realistic-interpolation models, which can be used in conjunction with a much wider class of (anti-aliasing) prefilters that are not necessarily ideal low-pass. We summarize and discuss the results available for the determination of the approximation error and of the sampling rate when the input of the system is essentially arbitrary; e.g., nonbandlimited. We also review variations of sampling that can be understood from the same unifying perspective. These include wavelets, multiwavelets, Papoulis generalized sampling, finite elements, and frames. Irregular sampling and radial basis functions are briefly mentioned.

1,384 citations

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TL;DR: A unified framework for uniform and nonuniform sampling and reconstruction in shift-invariant subspaces is provided by bringing together wavelet theory, frame theory, reproducing kernel Hilbert spaces, approximation theory, amalgam spaces, and sampling.

Abstract: This article discusses modern techniques for nonuniform sampling and reconstruction of functions in shift-invariant spaces. It is a survey as well as a research paper and provides a unified framework for uniform and nonuniform sampling and reconstruction in shift-invariant subspaces by bringing together wavelet theory, frame theory, reproducing kernel Hilbert spaces, approximation theory, amalgam spaces, and sampling. Inspired by applications taken from communication, astronomy, and medicine, the following aspects will be emphasized: (a) The sampling problem is well defined within the setting of shift-invariant spaces. (b) The general theory works in arbitrary dimension and for a broad class of generators. (c) The reconstruction of a function from any sufficiently dense nonuniform sampling set is obtained by efficient iterative algorithms. These algorithms converge geometrically and are robust in the presence of noise. (d) To model the natural decay conditions of real signals and images, the sampling theory is developed in weighted L p-spaces.

725 citations

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TL;DR: In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the continuous and the discrete transform are considered in turn.

Abstract: The wavelet transform has emerged over recent years as a powerful time-frequency analysis and signal coding tool favoured for the interrogation of complex nonstationary signals. Its application to biosignal processing has been at the forefront of these developments where it has been found particularly useful in the study of these, often problematic, signals: none more so than the ECG. In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the continuous and the discrete transform are considered in turn.

713 citations

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01 Apr 1987385 citations

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24 Aug 2008TL;DR: This work shows how a novel multi-resolution symbolic representation can be used to index datasets which are several orders of magnitude larger than anything else considered in the literature, allowing for the exact mining of truly massive real world datasets.

Abstract: Current research in indexing and mining time series data has produced many interesting algorithms and representations. However, the algorithms and the size of data considered have generally not been representative of the increasingly massive datasets encountered in science, engineering, and business domains. In this work, we show how a novel multi-resolution symbolic representation can be used to index datasets which are several orders of magnitude larger than anything else considered in the literature. Our approach allows both fast exact search and ultra fast approximate search. We show how to exploit the combination of both types of search as sub-routines in data mining algorithms, allowing for the exact mining of truly massive real world datasets, containing millions of time series.

340 citations