Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present, analyze, and numerically evaluate extended algorithms for detecting changes from an acting stochastic process to a number of possible alternatives. The algorithms are sequential, requiring minimal memory capacity and operational complexity, and they incorporate decision thresholds. The performance of the algorithms is controlled by the selection of the thresholds. Asymptotically, the first algorithmic extension detects the acting process correctly in an expected stopping time sense. In addition, the probability of error induced by a reinitialization algorithmic extension converges asymptotically to zero, when the acting process changes infrequently (with order inversely proportional to the value of the decision thresholds). The presented algorithmic systems are quite porful and their applications are numerous, ranging from industrial quality control to traffic and performance monitoring in highspeed networks.
['Anthony Burrell', 'Panayota Papantoni-Kazakos']
I am writing a research paper on a idea Extended sequential algorithms for detecting changes in acting stochastic processes
[{"from": "human", "value": "I am writing a research paper on a idea Extended sequential algorithms for detecting changes in acting stochastic processes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present, analyze, and numerically evaluate extended algorithms for detecting changes from an acting stochastic process to a number of possible alternatives. The algorithms are sequential, requiring minimal memory capacity and operational complexity, and they incorporate decision thresholds. The performance of the algorithms is controlled by the selection of the thresholds. Asymptotically, the first algorithmic extension detects the acting process correctly in an expected stopping time sense. In addition, the probability of error induced by a reinitialization algorithmic extension converges asymptotically to zero, when the acting process changes infrequently (with order inversely proportional to the value of the decision thresholds). The presented algorithmic systems are quite porful and their applications are numerous, ranging from industrial quality control to traffic and performance monitoring in highspeed networks."}]