Sentence examples for methods for compressed from inspiring English sources

As illustrative and evaluation examples, we formulate four particular applications under this framework: filtering for power line communications, estimation in sensor networks with noisy channels, reconstruction methods for compressed sensing, and fuzzy clustering.

As examples, four practical applications under this framework are presented: (1) filtering for power line communications, (2) estimation in sensor networks with noisy channels, (3) reconstruction methods for compressed sensing, and (4) fuzzy clustering.

This section presents four practical problems developed under the proposed framework: robust filtering for power line communications, robust estimation in sensor networks with noisy channels, robust reconstruction methods for compressed sensing, and robust fuzzy clustering.

Four particular applications are developed under this framework: robust filtering for power line communications, robust estimation in sensor networks with noisy channels, robust reconstruction methods for compressed sensing, and robust fuzzy clustering.

As examples, we formulate four practical applications under this framework: (1) filtering for power line communications, (2) estimation in sensor networks with noisy channels, (3) reconstruction methods for compressed sensing, and (4) fuzzy clustering.

Earlier this month, ITC Judge E. James Gildea ruled that Apple infringes US Patent 6,658,146 directed to systems and methods for compressing images and US Patent 6,683,978 directed to image data formats, both of which belong to S3 Graphics (and soon, to HTC).

This study provides a new optimization design method for compressed hydrogen cycling test system, has an important significance in development of high pressure hydrogen gas cycling test.

Scott MacKenzie, from York University, showed his H4-Writer, a four-key text input system that uses an established coding scheme (Huffman coding, a lossless method for compressing information, invented in 1952 by MIT student David Huffman) to translate key sequences to letter-symbols.

On the other hand, a method for compressing signaling message called SigComp [9] has been developed in the IETF.

Ann and Erenguc (1998) introduced activities compression, and Van Slyke was the first researcher who used the Monte Carlo simulation method for compressing activities.

In this work, a highly efficient, fast, scalable method for compressing motion capture clips is proposed by introducing a Linear Set Partitioning In Hierarchical Trees (LSPIHT) algorithm.