نتایج جستجو برای: convolutional

تعداد نتایج: 31503  

2018
Thomas Teh Chaiyawan Auepanwiriyakul John Alexander Harston A. Aldo Faisal

Deep Learning methods, specifically convolutional neural networks (CNNs), have seen a lot of success in the domain of image-based data, where the data offers a clearly structured topology in the regular lattice of pixels. This 4-neighbourhood topological simplicity makes the application of convolutional masks straightforward for time series data, such as video applications, but many high-dimens...

Journal: :CoRR 2014
Hilton Bristow Simon Lucey

Sparse and convolutional constraints form a natural prior for many optimization problems that arise from physical processes. Detecting motifs in speech and musical passages, super-resolving images, compressing videos, and reconstructing harmonic motions can all leverage redundancies introduced by convolution. Solving problems involving sparse and convolutional constraints remains a difficult co...

2004
Heide Gluesing-Luerssen Joachim Rosenthal

The generalized Singleton bound and MDS-convolutional codes are reviewed. For each n, k and 6 an elementary construction of rate k / n MDS convolutional codes of degree 6 is given.

1999
Joachim Rosenthal Eric V. York

Using a new parity-check matrix, a class of convolutional codes with a designed free distance is introduced. This new class of codes has many characteristics of BCH block codes, therefore, we call these codes BCH convolutional codes.

Journal: :Adv. in Math. of Comm. 2008
Sergio Estrada Juan Ramón García-Rozas Justo Peralta E. Sánchez-García

In this note we introduce the concept of group convolutional code. We make a complete classification of the minimal S 3-convolutional codes over the field of five elements by means of Jategaonkar's theorems .

Journal: :IEEE Trans. Information Theory 1999
Joachim Rosenthal Eric V. York

Using a new parity-check matrix, a class of convolutional codes with a designed free distance is introduced. This new class of codes has many characteristics of BCH block codes, therefore, we call these codes BCH convolutional codes.

2002
Michel Fliess

We are extending to linear recurrent codes, i.e., to time-varying convolutional codes, most of the classic structural properties of fixed convolutional codes. Those results are obtained thanks to a module-theoretic framework which has been developed in linear control.

Journal: :CoRR 2014
Alex Krizhevsky

I present a new way to parallelize the training of convolutional neural networks across multiple GPUs. The method scales significantly better than all alternatives when applied to modern convolutional neural

2003
Alexandre Graell i Amat Sergio Benedetto Guido Montorsi

Recently, we proposed a new design technique to construct high-rate convolutional codes based on a structure formed by a block encoder and a simpler convolutional encoder [1]. The search technique was based on the optimization of the output weight enumerating function of the code. Here, we prove that every (n, n − 1) convolutional code can be reduced to this structure. Following this result and...

Journal: :CoRR 2018
Xiaotong Lu Weisheng Dong Peiyao Wang Guangming Shi Xuemei Xie

Compressive sensing (CS), aiming to reconstruct an image/signal from a small set of random measurements has attracted considerable attentions in recent years. Due to the high dimensionality of images, previous CS methods mainly work on image blocks to avoid the huge requirements of memory and computation, i.e., image blocks are measured with Gaussian random matrices, and the whole images are re...

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