Performance Dependence of Single-Carrier Digital Back-Propagation on Fiber Types and Data Rates

2014 ◽  
Author(s):  
Antonio Napoli ◽  
Danish Rafique ◽  
Bernhard Spinnler ◽  
Maxim Kuschnerov ◽  
Markus Noelle ◽  
...  
Keyword(s):  
Back Propagation ◽  
Fiber Types ◽  
Single Carrier ◽  
Data Rates

Comparison of single carrier and OFDM with back-propagation and RF pilot tone for a 9×224Gb/s POLMUX-16QAM system

2011 ◽  
Author(s):  
A. Diaz ◽  
Z. Maalej ◽  
A. Lobato ◽  
S. Adhikari ◽  
E. Timmers ◽  
...  
Keyword(s):  
Back Propagation ◽  
Single Carrier

Single Carrier High Symbol Rate Transmitter for Data Rates up to 1.0 Tb/s

2016 ◽  
Author(s):  
G. Raybon ◽  
J. Cho ◽  
A. Adamiecki ◽  
P. Winzer ◽  
A. Konczykowska ◽  
...  
Keyword(s):  
Single Carrier ◽  
Data Rates ◽  
Symbol Rate

scholarly journals Multi-code Multicarrier CDMA: Performance Analysis

2017 ◽  
Vol 2 (1) ◽  
pp. 12
Author(s):  
Taeyoon Kim ◽  
Jeffrey G. Andrews ◽  
Jaeweon Kim ◽  
Theodore S. Rappaport
Keyword(s):  
Multiple Access ◽  
Multiple Access Interference ◽  
Cellular Systems ◽  
Cdma System ◽  
Multicarrier Cdma ◽  
Selective Fading ◽  
Next Generation ◽  
Single Carrier ◽  
Data Rates ◽  
Code Division Multiple

A new multi-code multicarrier code division multiple access (MC-MC-CDMA) system is proposed and analyzed in afrequency selective fading channel. By allowing each user to transmit an M-ary code sequence, the proposed MC-MC-CDMA system can support various data rates as required by next generation standards without increasing the interference which is common in general multicarrier CDMA systems. The bit error rate of the system is analytically derived in frequency selective fading, with Gaussian noise and multiple access interference. The results show that the proposed MC-MC-CDMA system clearly outperforms both single-code multicarrier CDMA (MC-CDMA) and single-carrier multi-code CDMA in a fixed bandwidth allocation.This indicates that MC-MC-CDMA can be considered for next generation cellular systems.

Switching of Wavelet Transforms by Neural Network for Image Compression

2018 ◽  
Vol 16 (1) ◽  
pp. 43-56
Author(s):  
Houda Chakib ◽  
Brahim Minaoui ◽  
Abderrahim Salhi ◽  
Imad Badi
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Wavelet Transforms ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
High Data ◽  
Transmission Cost ◽  
Ideal Image ◽  
Data Rates ◽  
Significant Attention

Nowadays, digital images compression requires more and more significant attention of researchers. Even when high data rates are available, image compression is necessary in order to reduce the memory used, as well the transmission cost. An ideal image compression system must yield high-quality compressed image with high compression ratio. In this article, a neural network is implemented for image compression using the feature of wavelet transform. The idea is that a back-propagation neural network can be trained to relate the image contents to its ideal compression method between two different wavelet transforms: orthogonal (Haar) and biorthogonal (bior4.4).

Structural Organization and Distribution of Fiber Types in Extraocular Muscles of Cats

1972 ◽  
Vol 30 ◽  
pp. 34-35
Author(s):  
Asish C. Nag ◽  
Lee D. Peachey
Keyword(s):  
Fiber Type ◽  
Light And Electron Microscopy ◽  
Small Diameter ◽  
Extraocular Muscles ◽  
Fiber Types ◽  
Distinctive Features ◽  
Superior Rectus ◽  
Adult Cats ◽  
Different Diameters ◽  
Orbital Region

Cat extraocular muscles consist of two regions: orbital, and global. The orbital region contains predominantly small diameter fibers, while the global region contains a variety of fibers of different diameters. The differences in ultrastructural features among these muscle fibers indicate that the extraocular muscles of cats contain at least five structurally distinguishable types of fibers.Superior rectus muscles were studied by light and electron microscopy, mapping the distribution of each fiber type with its distinctive features. A mixture of 4% paraformaldehyde and 4% glutaraldehyde was perfused through the carotid arteries of anesthetized adult cats and applied locally to exposed superior rectus muscles during the perfusion.

Use of EDS mapping to characterize thermochemical stability of fibers in intermetallic matrix composites

1992 ◽  
Vol 50 (1) ◽  
pp. 160-161
Author(s):  
John R. Porter
Keyword(s):  
Spatial Information ◽  
Beam Current ◽  
Fiber Types ◽  
Ceramic Fibers ◽  
Dye Transfer ◽  
Science Center ◽  
Commercial Development ◽  
Nih Image ◽  
Intermetallic Matrix Composites ◽  
Thermochemical Stability

New ceramic fibers, currently in various stages of commercial development, have been consolidated in intermetallic matrices such as γ-TiAl and FeAl. Fiber types include SiC, TiB2 and polycrystalline and single crystal Al2O3. This work required the development of techniques to characterize the thermochemical stability of these fibers in different matrices.SEM/EDS elemental mapping was used for this work. To obtain qualitative compositional/spatial information, the best realistically achievable counting statistics were required. We established that 128 × 128 maps, acquired with a 20 KeV accelerating voltage, 3 sec. live time per pixel (total mapping time, 18 h) and with beam current adjusted to give 30% dead time, provided adequate image quality at a magnification of 800X. The maps were acquired, with backgrounds subtracted, using a Noran TN 5500 EDS system. The images and maps were transferred to a Macintosh and converted into TIFF files using either TIFF Maker, or TNtolMAGE, a Microsoft QuickBASIC program developed at the Science Center. From TIFF files, images and maps were opened in either NIH Image or Adobe Photoshop for processing and analysis and printed from Microsoft Powerpoint on a Kodak XL7700 dye transfer image printer.

Using Connectionist Modules for Decision Support

1990 ◽  
Vol 29 (03) ◽  
pp. 167-181 ◽  
Author(s):  
G. Hripcsak
Keyword(s):  
Decision Support ◽  
Standard Deviation ◽  
Confidence Interval ◽  
Posterior Probability ◽  
Back Propagation ◽  
Connectionist Model ◽  
Test Set ◽  
The Third ◽  
Independent Test ◽  
Better Than

AbstractA connectionist model for decision support was constructed out of several back-propagation modules. Manifestations serve as input to the model; they may be real-valued, and the confidence in their measurement may be specified. The model produces as its output the posterior probability of disease. The model was trained on 1,000 cases taken from a simulated underlying population with three conditionally independent manifestations. The first manifestation had a linear relationship between value and posterior probability of disease, the second had a stepped relationship, and the third was normally distributed. An independent test set of 30,000 cases showed that the model was better able to estimate the posterior probability of disease (the standard deviation of residuals was 0.046, with a 95% confidence interval of 0.046-0.047) than a model constructed using logistic regression (with a standard deviation of residuals of 0.062, with a 95% confidence interval of 0.062-0.063). The model fitted the normal and stepped manifestations better than the linear one. It accommodated intermediate levels of confidence well.

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