✦ LIBER ✦

Neural network as generalized transversal filters

✍ Scribed by Min I. Chung

Publisher: Elsevier Science
Year: 1988
Tongue: English
Weight: 46 KB
Volume: 1
Category: Article
ISSN: 0893-6080
DOI: 10.1016/0893-6080(88)90326-7

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Median and neural network hybrid (MNNH)

Median and neural network hybrid (MNNH) filters

✍ Akira Taguchi; Mitsuji Muneyasu; Takao Hinamoto 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 409 KB

When a nonstationary signal containing sudden changes, such as an image signal, is degraded by an additive noise, a powerful means to recover the signal is to use a nonlinear filter. This paper uses a layered neural network, and proposes a new method to construct a nonlinear filter for restoring a s

Development of a generalized neural netw

Development of a generalized neural network

✍ Greger G Andersson; Peter Kaufmann 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 162 KB

The interest for neural networks has grown concomitantly with the increased awareness of the ubiquity of non-linear systems. The main focus on improvements in this field has been on the development of different algorithms that either speed up the convergence rate andror avoid entrapment in local min

Filtering and unfolding using neural net

Filtering and unfolding using neural networks

✍ Thomas Lindblad; Géza Székely 📂 Article 📅 1993 🏛 Elsevier Science 🌐 English ⚖ 286 KB

Cellular neural networks as a general ma

Cellular neural networks as a general massively parallel computational paradigm

✍ Destri, Giulio; Marenzoni, Paolo 📂 Article 📅 1996 🏛 John Wiley and Sons 🌐 English ⚖ 896 KB

In this paper is presented the use of the discrete-time cellular neural network (DTCNN) paradigm to develop algorithms devised for general-purpose massively parallel processing (MPP) systems. This paradigm is defined in discrete N-dimensional spaces (lattices) and is characterized by the locality of

Generalized part family formation using

Generalized part family formation using neural network techniques

✍ Y.B. Moon; S.C. Chi 📂 Article 📅 1992 🏛 Society of Manufacturing Engineers 🌐 English ⚖ 865 KB

Fourier analysis of the generalized CMAC

Fourier analysis of the generalized CMAC neural network

✍ Francisco J González-Serrano; Anı́bal R Figueiras-Vidal; Antonio Artés-Rodriguez 📂 Article 📅 1998 🏛 Elsevier Science 🌐 English ⚖ 90 KB

The Cerebellar Model Articulation Controller (CMAC) is a simple and fast neural network: these characteristics have extended its successful applications, while the analysis of its representation capabilities, as for many other neural networks, did not follow a similar development. In this article w