Invention Grant
- Patent Title: System and method for learning-based lossless data compression
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Application No.: US18623018Application Date: 2024-03-31
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Publication No.: US12119848B1Publication Date: 2024-10-15
- Inventor: Zhu Li , Paras Maharjan
- Applicant: AtomBeam Technologies Inc.
- Applicant Address: US CA Moraga
- Assignee: ATOMBEAM TECHNOLOGIES INC.
- Current Assignee: ATOMBEAM TECHNOLOGIES INC.
- Current Assignee Address: US CA Moraga
- Agency: Galvin Patent Law LLC
- Agent Brian R. Galvin
- Main IPC: H03M7/00
- IPC: H03M7/00 ; H03M7/30

Abstract:
A system and method learning-based lossless data compression. The system and method proposed allow for fast and efficient lossless data compression of a large variety of data types. The system and method have a variety of real-world applications, including deep learning solutions for telemetry, tracking, and command subsystems for satellites. Satellites and their control centers are incredibly spaced apart which makes data compression an extremely important process to transmit large sets of information in a low-latency, high-efficiency environment. The proposed system and method utilize probability prediction driven arithmetic coding which provides faster encoding times and higher compression ratios when paired with a long short-term memory system for data compression.
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