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The two most common memory errors are repeatable errors (also known as hard errors) and transient errors (also called soft errors). A hard error occurs when a memory module is defective; because of its physical flaw, the memory consistently returns the same erroneous results. For example, a memory cell might become damaged because of power surges or electrostatic discharge (ESD) and be stuck in a state that reads as a 1. This could cause parity errors or simply just return the wrong data. A hard memory error can also be the result of a loose memory module, a system board defect, or a defective or blown memory chip. In most cases, hard errors are relatively easy to diagnose and fix because they are not intermittent. Hard errors are consistent and repeated, allowing you a better chance to isolate the source of the problem. A transient error, or soft error, occurs when a bit provides the wrong data value one time or intermittently but otherwise continues to function correctly. Because these errors are moving targets, they are much harder to diagnose. In most cases, soft memory errors are usually the result of poor quality memory, motherboards, or ESD . . . and not necessarily the physical memory chip itself. The system timing could be too fast for the memory or vice versa. Or the stray radioactivity

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This construction of gZin the un-regularized case is depicted in Fig. 32.4. In the figure, the arrows indicate that results from projecting y onto R ( H ) and results from projecting h onto R(H).

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Traf c characterization is the rst task of traf c engineering measurements as de ned by [LCT + 02], having the following goals: Identifying variations in traf c patterns using statistical analysis, including development of traf c pro les to capture daily, weekly, or seasonal variations. Determining traf c distributions in the network on the basis of ows, interfaces, links, nodes, node-pairs, paths, or destinations. Estimation of the traf c load according to service classes in different routers and the network. Observing trends for traf c growth and forecasting of traf c demands.

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30 S Amari, T-P Chen, and A Cichocki Non-holonomic constraints in learning algorithms for blind source separation Neural Computation, 12:1463 1484, 2000 31 S Amari and A Cichocki Adaptive blind signal processing - neural network approaches Proceedings IEEE, 86:1186 1187, 1998 32 S Amari, A Cichocki, and HH Yang Recurrent neural networks for blind separation of sources In in Proc Int Symposium Nonlinear Theory and its Applications NOLTA-95 Las Vegas, volume 1, pages 37 42, Dec 1995 33 S Amari, A Cichocki, and HH Yang A new learning algorithm for blind signal separation In Michakel C Mozer David S Touretzky and Michael E Hasselmo, editors, Advances in Neural Information Processing Systems 1995, volume 8, pages 757 763 MIT Press: Cambridge, MA, 1996 34 S Amari, A Cichocki, and HH Yang Unsupervised Adaptive Filtering, chapter Blind Signal Separation and Extraction - Neural and Information Theoretic Approaches.

to 100 MHz CPU bus speeds, and includes a high-performance RAM controller, a 64-bit ECC/parity memory bus interface, an AGP interface, and device controllers for IDE, USB, and PS/2, as well as a Super I/O controller. For more information on ALi s chipset products, visit www.ali.com.tw.

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John Wiley, 1999 35 S Amari and SC Douglas Why natural gradient In Proc IEEE International Conference Acoustics, Speech, Signal Processing, volume II, pages 1213 1216, Seattle, WA, May 1998 36 S Amari, SC Douglas, and A Cichocki Multichannel blind deconvolution and source separation using the natural gradient In submitted to IEEE Trans Signal Processing, September 1997 37 S Amari, SC Douglas, and A Cichocki Information geometry of blind source deconvolution In presented at Mathematical Theory of Networks and Systems, Padova, Italy, July 1998 38 S Amari, SC Douglas, A Cichocki, and HH Yang Multichannel blind deconvolution and equalization using the natural gradient In Proc IEEE Workshop on Signal Processing Advances in Wireless Communications, pages 101 104, Paris, France, April 1997 39 S Amari, SC Douglas, A Cichocki, and HH Yang.

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