Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  consider the problem of block-size selection to achieve a desired probability of error for universal source coding. While Baron, et al. (2004; 1973) studied this question for rates in the vicinity of entropy for known distributions using central-limit-theorem techniques,  are interested in all rates for unknown distributions and use error-exponent techniques. By adapting a technique of Gallager from the exercises of Gallager (1971),  derive a universal lor bound to the source-coding error exponent that depends only on the alphabet size and is quadratic in the gap to entropy.
['Cheng Chang', 'Anant Sahai']
I am writing a research paper on a idea Universal Quadratic Lower Bounds on Source Coding Error Exponents
[{"from": "human", "value": "I am writing a research paper on a idea Universal Quadratic Lower Bounds on Source Coding Error Exponents"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  consider the problem of block-size selection to achieve a desired probability of error for universal source coding. While Baron, et al. (2004; 1973) studied this question for rates in the vicinity of entropy for known distributions using central-limit-theorem techniques,  are interested in all rates for unknown distributions and use error-exponent techniques. By adapting a technique of Gallager from the exercises of Gallager (1971),  derive a universal lor bound to the source-coding error exponent that depends only on the alphabet size and is quadratic in the gap to entropy."}]