Group - Recurrent pyogenic cholangitis

Flexible CO2 laser fibers enable new treatment for papilloma patients in an offi...

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Survival in recurrent glioblastoma multiforme was extended without major toxicit...

About the Video: In this interview with Ellen Beth Levitt, melanoma expert Dr. S...

About the Video: In this interview with Ellen Beth Levitt, melanoma expert Dr. S...

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BOOK REVIEW

THE RULE OF LAW: Perspectives From Around the Globe

In mathematics, a recurrent point for function f is a point that is in the limit set of the iterated function f. Any neighborhood containing the recurrent point will also contain (a countable number of) iterates of it as well.

Recurrent rotation refers to a group of songs still frequently aired on a contemporary hit radio station even several months after the initial debut. It is also used to describe core songs in other radio formats as well.

Recurrent Brief Depression (RBD) defines a mental disorder characterized by intermittent depressive episodes, in women not related to menstrual cycles, occurring at least once a month over at least one year or more fulfilling the diagnostic criteria for major depressive episodes (DSM-IV and ICD-10) except for duration which in RBD is less than 14 days, typically 2–4 days. Despite the short duration of the depressive episodes, such episodes are severe and suicidal ideation and impaired function is rather common.

Chronic recurrent erysipelas is a cutaneous condition with several predisposing factors including alcoholism, diabetes, and tinea pedis.

Recurrent Airway Obstruction, also known as Chronic Obstructive Pulmonary Disorder or broken wind is a respiratory disease in horses. Also known as heaves.

Equine Recurrent (Periodic) Uveitis, ("Moon Blindness", Recurrent Iridocyclitis) is an acute, non-granulomatous inflammation of the uveal tract of the eye, occurring commonly in horses of all breeds, worldwide. The causative factor is not known, but several pathogeneses have been suggested.

Recurrent palmoplantar hidradenitis (also known as "Idiopathic plantar hidradenitis") is primarily a disorder of healthy children and young adults, characterized by lesions that are primarily painful, subcutaneous nodules on the plantar surface, resembling erythema nodosum.James, William; Berger, Timothy; Elston, Dirk (2005).

Disseminate and recurrent infundibulofolliculitis presents with irregularly shaped papules pierced by hair, mildly pruritic at times, and is chronic with recurrent exacerbations.James, William; Berger, Timothy; Elston, Dirk (2005).

Heubner's artery (also known as the recurrent artery of Heubner), named after the German paediatrician Otto Heubner is a branch from the anterior cerebral artery, typically from the distal A1 segment or proximal A2 segment. Its vascular territory is the anteromedial section of the caudate nucleus and the anterioinferior section of the internal capsule.

Abstract: University Hospital of Nottingham, England.

Abstract: University Hospital of Nottingham, England.

Abstract: In this paper the recurrent back-propagation and Newton algorithms for an important class of recurrent networks and their convergence properties are discussed. To ensure proper convergence behavior, recurrent connections must be suitably constrained during the learning process. Simulation results demonstrate that the algorithms with the suggested constraint have superior performance. 1. INTRODUCTION It is well known that feedforward neural networks may have difficulties in representing the sequential behavior of a target sequence and can perform only passive cognition. 4,13 This deficiency ham...

Abstract: In this paper the recurrent back-propagation and Newton algorithms for an important class of recurrent networks and their convergence properties are discussed. To ensure proper convergence behavior, recurrent connections must be suitably constrained during the learning process. Simulation results demonstrate that the algorithms with the suggested constraint have superior performance. 1. INTRODUCTION It is well known that feedforward neural networks may have difficulties in representing the sequential behavior of a target sequence and can perform only passive cognition. 4,13 This deficiency ham...

Abstract: In this paper the recurrent back-propagation and Newton algorithms for an important class of recurrent networks and their convergence properties are discussed. To ensure proper convergence behavior, recurrent connections must be suitably constrained during the learning process. Simulation results demonstrate that the algorithms with the suggested constraint have superior performance. 1. INTRODUCTION It is well known that feedforward neural networks may have difficulties in representing the sequential behavior of a target sequence and can perform only passive cognition. 4,13 This deficiency ham...

Abstract: Abstract The recurrent neural network is a kind of neural network with one or more feedback loops. We may have feedback from the output neurons of the multilayer to the input layer. Yet another possible form of feedback is from the hidden neurons of the network to the input layer. In this paper, we propose a channel equalization scheme using a decision feedback recurrent neural network, which has feedback loops from both the hidden layer and the decision part, with real-time recurrent network. Simulation results show that the proposed scheme outperforms the recurrent neural network that only ...

Abstract: In this paper the recurrent back-propagation and Newton algorithms for an important class of recurrent networks and their convergence properties are discussed. To ensure proper convergence behavior, recurrent connections must be suitably constrained during the learning process. Simulation results demonstrate that the algorithms with the suggested constraint have superior performance. 1. INTRODUCTION It is well known that feedforward neural networks may have difficulties in representing the sequential behavior of a target sequence and can perform only passive cognition. 4,13 This deficiency ham...

Abstract: Abstract Giles et al. (1995) have proven that Fahlman's recurrent cascade correlation (RCC) architecture is not capable of realizing finite state automata that have state-cycles of length more than two under a constant input signal. This paper extends the conclusions of Giles et al. by showing that there exists a corollary to their original proof which identifies a large second class of automata, that is also unrepresentable by RCC

Abstract: A broad approach isdeveloped for training dynamical behaviors in connectionist networks. General recurrent networks are powerful computational devices, necessary for di cult tasks like constraint satisfaction and temporal processing. These tasks are discussed here in some detail. From both theoretical and empirical considerations, it is concluded that such tasks are best addressed by recurrent networks that operate continuously in time|and further, that e ective learning rules for these continuous-time networks must be able to prescribe their dynamical properties. A general class of such learn...

Abstract: Abstract Very often, recurrent neural networks are used to model dynamic, nonlinear relationships. However, particularly in many technical applications recurrent networks do not perform noticeably better than static networks (like e.g. Multilayer Perceptrons) processing only the current input pattern. The main reason for this observation is that the networks have to cope with noisy input and sometimes even noisy output data. Large weights in recurrent connections may cause stability problems and with small weights temporal information cannot be considered in an appropriate way. This paper dem...