PubMed · 13911637
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M W SHELLY. 1961. Learning with reduced feedback information.. https://doi.org/10.1037/h0049045
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This paper presents two feedback neural networks for solving a nonlinear and mixed complementarity problem. The first feedback neural network is designed to solve the strictly monotone problem. This one has no parameter and possesses a very simple structure for implementation in hardware. Based on a new idea, the second feedback neural network for solving the monotone problem is constructed by using the first one as a subnetwork. This feedback neural network has the least number of state variables. The stability of a solution of the problem is proved. When the problem is strictly monotone, the unique solution is uniformly and asymptotically stable in the large. When the problem has many solutions, it is guaranteed that, for any initial point, the trajectory of the network does converge to an exact solution of the problem. Feasibility and efficiency of the proposed neural networks are supported by simulation experiments. Moreover, the feedback neural network can also be applied to solve general nonlinear convex programming and nonlinear monotone variational inequalities problems with convex constraints.
Norris et al. recently reported experimental evidence that listeners learn phoneme categories in response to lexical feedback. To reconcile these findings with their modular account of speech perception, the authors argue that top-down feedback can be used to support phoneme learning, but not to influence on-line phonemic processing. We suggest that these findings have broader implications than the authors assume, and we discuss potential challenges for integrating a modular theory with top-down learning.
BACKGROUND: Audit and feedback systems have significantly improved medical care in numerous settings, and they appear to work by stimulating competition rather than through command and control. METHODS: The West Virginia Medical Institute (WVMI), a Medicare-designated Quality Improvement Organization (QIO), periodically collected quality information on five common conditions (acute myocardial infarction [AMI], heart failure, pneumonia, stroke, and atrial fibrillation) that cause hospitalization in Medicare beneficiaries. All 44 acute care hospitals in West Virginia were offered written and orally presented reports of quality performance from 1998 through 2001. RESULTS: All indicators appeared to improve statewide. Several--for example, aspirin at discharge for AMI patients and pneumococcal vaccine for pneumonia patients--improved by more than 10 absolute percentage points. Fourteen of 15 quality indicators showed significant improvement (p < .05, paired t-test) in all hospitals between the before- and after-feedback periods. Seven of 13 indicators assessed during the entire study in the largest hospitals showed no significant trends in quality before feedback but significant increases (p < .05, chi-square for trend) in the after-feedback period. DISCUSSION: The quality indicator changes reported can represent important health gains for West Virginia Medicare beneficiaries. Most of the improvement did not occur until after hospitals received feedback.