Statistical Mechanical Approach to Lossy Data Compression:Theory and Practice

The encoder and decoder for lossy data compression of binary memoryless sources are developed on the basis of a specific-type nonmonotonic perceptron. Statistical mechanical analysis indicates that the potential ability of the perceptron-based code saturates the theoretically achievable limit in most cases although exactly performing the compression is computationally difficult. To resolve this difficulty, we provide a computationally tractable approximation algorithm using belief propagation (BP), which is a current standard algorithm of probabilistic inference. Introducing several approximations and heuristics, the BP-based algorithm exhibits performance that is close to the achievable limit in a practical time scale in optimal cases.Comment: 10 pages, 2 figures, REVTEX preprin

Control of peroxyoxalate chemiluminescence by nitrogen-containing ligand quenching: turning off and on by ligand-metal ion host-guest interactions

ArticleTETRAHEDRON. 67(36):6927-6933 (2011)journal articl

Statistical mechanics of lossy data compression using a non-monotonic perceptron

The performance of a lossy data compression scheme for uniformly biased Boolean messages is investigated via methods of statistical mechanics. Inspired by a formal similarity to the storage capacity problem in the research of neural networks, we utilize a perceptron of which the transfer function is appropriately designed in order to compress and decode the messages. Employing the replica method, we analytically show that our scheme can achieve the optimal performance known in the framework of lossy compression in most cases when the code length becomes infinity. The validity of the obtained results is numerically confirmed.Comment: 9 pages, 5 figures, Physical Review

Prevalence and Comorbidity of Anxiety and Depressive Disorders in Studies of PRIME-MD and PHQ (Patient Health Questionnaire) in Japan

We examine two studies on the prevalence and comorbidity of anxiety and depressive disorders in Japanese patients in primary care settings. The PRIME-MD study (Primary Care Evaluation of Mental Disorders) in Japan was conducted in seven primary care sites. The sample group included 601 adult patients (249 males, 352 females, mean age = 58.9 years, SD = 16.5). Of the 12.5% of patients diagnosed with mood disorders, 5.0% (n = 29) were major depressive disorder, and 6.7% (n = 40) were minor depressive disorder. The odds ratio for co-occurrence of major depressive disorder with generalized anxiety disorders and major depressive disorder with anxiety disorders (NOS) was 11.5 (95% CI: 2.17–18.45) and 8.00 (95% CI: 3.19–20.07), respectively. The PHQ (Patient Health Questionnaire) study in Japan was conducted in eleven primary care sites. A total of 1409 adult patients (611 males, 797 females; mean age: 56.2 years, SD: ±20.4) completed the PHQ in full. The prevalence of diagnosis of any mood disorder or any anxiety disorder was 25.0%. Of the 15.8% of patients diagnosed with mood disorders, 5.3% were for major depression and 8.4% for other depressive disorders. The odds ratio for co-occurrence of major depressive disorder with other anxiety disorders was 30.4 (95% CI: 13.19–70.28)

Control of peroxyoxalate chemiluminescence by nitrogen-containing ligand quenching: turning off and on by ligand–metal ion host–guest interactions

ArticleTETRAHEDRON. 67(36):6927-6933 (2011)journal articl

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)