Compression algorithms for speech, audio, still images, and video are quite complicated and, more importantly, nearly always lossy. Thus, samples often change dramatically once they’re decompressed.

With the rapid growth of the volume of image data, the burden of storage and transmission has increased dramatically. However, current algorithms face challenges in balancing compression efficiency ...

When trying to debug quantum hardware and software with a quantum simulator, every quantum bit (qubit) counts. Every simulated qubit closer to physical machine sizes halves the gap in computing power ...

The goal of digital compression algorithms is to produce a digital representation of an audio signal which, when decoded and reproduced, sounds the same as the original signal, while using a minimum ...

Compression reduces bandwidth and storage requirements by removing redundancy and irrelevancy. Redundancy occurs when data is sent when it’s not needed. Irrelevancy frequently occurs in audio and ...

The general development of information and communication technologies manifests in medicine as well and contributes to improvement of health care worldwide. It is very important nowadays when we are ...

The “middle-out” algorithm that has its roots in the most infamous (and probably funniest) scene in HBO’s “Silicon Valley” may have been fictional, but something like it can be found in Lepton, a cool ...