Abstract: A method and system for detecting and processing armed triggers associated with specific call functions in an intelligent network, using a distributed intelligent network triggering architecture. The complex trigger profile is removed from call processing at the service switching point to a trigger processing server, so that a much simplified and reduced profile can be sent to the service switching point associated with a roaming subscriber, which overcomes the problem of lack of support for long messages within the signalling infrastructure, and the problems associated with wide variation in the capabilities of service switching points. The reduced processing at the service switching point means that the detection points for armed triggers residing therein need only have a minimal triggering capability and a generic trigger for each detection point, and therefore do not need to be upgraded as new triggers are defined or as new criteria are defined for existing triggers at a given detection point.

Abstract: A Low-complexity and Low-memory Entropy Coder is proposed for image compression. It includes zerotree coding, followed by the use of Golomb-Rice codes to code the result in a VLC/VLI manner. The result is a complexity similar to that of JPEG coding. The proposed algorithm does not require use of any Huffman table, significant/insignificant list or arithmetic coding and therefore its memory requirement is minimized with respect to any known image entropy coder. Experimental results are given of the use of the proposed coder. The proposed coder is suitable for parallel processing implementation, ROI (Region Of Interest) coding and as a universal entropy coder for DCT and DWT.