Information theory provides the fundamental framework for understanding and designing data compression algorithms. At its core lies the concept of entropy, a quantitative measure that reflects the ...

Fuzzy transforms (F-transforms) are a class of fuzzy approximation methods that utilise fuzzy partitions to represent and reconstruct functions through a collection of weighted average values. By ...

“Irregular applications, such as graph analytics and sparse linear algebra, exhibit frequent indirect, data-dependent accesses to single or short sequences of elements that cause high main memory ...

Efficient data compression and transmission are crucial in space missions due to restricted resources, such as bandwidth and storage capacity. This requires efficient data-compression methods that ...

Optimizing data compression methods has become more critical than ever for cloud storage, data management, and streaming applications. Working with compressed data reduces network bandwidth, data ...

Compression, as the name implies, squeezes or “compresses” the size of a file or data set. Compression techniques are used for voice, video, audio, text, and program data in hundreds of different ...

Two broad categories of compression are currently in use. In lossy compression, data is intentionally discarded. As a result, the decompression of the data doesn't exactly match the original data.

IBM has entered into a definitive agreement to acquire Storwize, a privately held provider of real-time data compression technology. Storwize, based in Marlborough, Mass., builds solutions intended to ...

The latest release of Cisco’s WAN optimization product line — Wide Area Application Services (WAAS) 4.4 — proves that the company famous for routing packets can also shape, optimize and accelerate ...