Novel simple decision stage of Pan & Tompkins QRS detector and its FPGA-Based implementation

2012 ◽  
Author(s):  
El Hassan El Mimouni ◽  
Mohammed Karim
Keyword(s):  
Decision Stage

The Effect of Voluntary Disclosure on Investment Inefficiency

2020 ◽  
pp. 0000-0000 ◽  
Author(s):  
Ilan Guttman ◽  
Xiaojing Meng
Keyword(s):  
Cash Flow ◽  
Information Acquisition ◽  
Voluntary Disclosure ◽  
Efficiency Loss ◽  
Decision Stage ◽  
Choice Decision

We introduce real decisions (a project choice decision, an investment scale decision, and an information acquisition decision) to the Dye (1985) voluntary disclosure framework and examine how the prospect of voluntary disclosure affects managers' real decisions. Riskier projects lead to more volatile environment and hence entail higher efficiency loss at the subsequent investment scale decision stage if managers are uninformed. If managers are informed, they can withhold bad information, and the value of this option is higher for riskier projects. We show that the voluntary nature of managers' disclosure may lead to two types of inefficiencies: (1) managers may choose riskier projects, which generate lower expected cash flow due to the higher efficiency loss at the subsequent decision stage, and (2) managers may overinvest in information acquisition, because informed managers with bad information have the option to pool with uninformed mangers and benefit from being overpriced.

scholarly journals Location and Design of Urban Facilities considering Competitors’ Responses: A Case Study of Putuo District, Shanghai

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zhizhu Lai ◽  
Ge Yan ◽  
Yulong Chen ◽  
Zheng Wang
Keyword(s):  
Market Share ◽  
Probability Model ◽  
Shopping Mall ◽  
Decision Making Process ◽  
Location Decision ◽  
Decision Stage ◽  
Competitive Facility Location ◽  
Quality Decision ◽  
New Facility

In view of the problem of competitive facility location in urban planning, the response of competitors to the new facility is considered. We use Huff’s probability model to describe the market share of all facilities which depends on its service quality and its distance from customers. To maximize the market share of facilities, a two-stage method (quality decision stage and location decision stage) is adopted, which takes into account the responses of competitors. In the stage of quality decision, the competitive decision-making process is simulated as a game process and solved by Nash equilibrium. The solution of the quality decision process can be expressed as a function of the new facility’s location which can be obtained by polynomial approximation. In the location decision stage, we apply the interval analysis based on branch and bound algorithm to determine the optimal location of new facility. Then, we use the randomly generated numerical experiment to verify the effectiveness of the model and algorithm. Finally, we apply this model and algorithm to the location of a new shopping mall in Putuo district, Shanghai.

Features and feedback

2000 ◽  
Vol 23 (3) ◽  
pp. 328-329
Author(s):  
Tobey L. Doeleman ◽  
Joan A. Sereno ◽  
Allard Jongman ◽  
Sara C. Sereno
Keyword(s):  
Word Recognition ◽  
Decision Stage

Our commentary outlines a number of arguments questioning an autonomous model of word recognition without feedback. Arguments are presented against the need for a phonemic decision stage and in support of a featural level in a model including feedback.

Reward-Modulated Hebbian Learning of Decision Making

2010 ◽  
Vol 22 (6) ◽  
pp. 1399-1444 ◽  
Author(s):  
Michael Pfeiffer ◽  
Bernhard Nessler ◽  
Rodney J. Douglas ◽  
Wolfgang Maass
Keyword(s):  
Decision Making ◽  
Hebbian Learning ◽  
Learning Rule ◽  
Final Decision ◽  
Bayesian Decision ◽  
Decision Stage ◽  
Fast Learning ◽  
Hebb Rule ◽  
Adaptive Processes ◽  
Perceptron Learning

We introduce a framework for decision making in which the learning of decision making is reduced to its simplest and biologically most plausible form: Hebbian learning on a linear neuron. We cast our Bayesian-Hebb learning rule as reinforcement learning in which certain decisions are rewarded and prove that each synaptic weight will on average converge exponentially fast to the log-odd of receiving a reward when its pre- and postsynaptic neurons are active. In our simple architecture, a particular action is selected from the set of candidate actions by a winner-take-all operation. The global reward assigned to this action then modulates the update of each synapse. Apart from this global reward signal, our reward-modulated Bayesian Hebb rule is a pure Hebb update that depends only on the coactivation of the pre- and postsynaptic neurons, not on the weighted sum of all presynaptic inputs to the postsynaptic neuron as in the perceptron learning rule or the Rescorla-Wagner rule. This simple approach to action-selection learning requires that information about sensory inputs be presented to the Bayesian decision stage in a suitably preprocessed form resulting from other adaptive processes (acting on a larger timescale) that detect salient dependencies among input features. Hence our proposed framework for fast learning of decisions also provides interesting new hypotheses regarding neural nodes and computational goals of cortical areas that provide input to the final decision stage.

The Staged Nature of Decision Making among Senior Tourists

2019 ◽  
Vol 59 (4) ◽  
pp. 602-613 ◽  
Author(s):  
Juan Luis Nicolau ◽  
Nieves Losada ◽  
Elisa Alén ◽  
Trinidad Domínguez
Keyword(s):  
Decision Making ◽  
Decision Making Process ◽  
Social Character ◽  
Two Stage ◽  
Decision Stage ◽  
Proposed Model ◽  
The Social ◽  
The Individual ◽  
The Way

This article builds on the idea that senior tourists’ decision making is a staged process in which the different choices are sequential, interrelated, and interdependent. These decisions are “whether to take a vacation," “whether to opt for an international trip," “whether to use an organized tour," and “whether to use publicly subsidized travel.” Considering the social character of many trips offered to seniors, the fourth decision of the proposed process makes it unique. No research has empirically considered using a staged decision making in the context of senior travelers, and the proposed model quantifies the effect of each variable based on the decision the individual is dealing with; also, the way a variable changes its effect even within the same decision stage depending on the individual is analyzed by including heterogeneity into the modeling. The results find that senior tourists follow the proposed four-staged decision-making process rather than the basic two-stage decision-making process.

Incumbent and non-incumbent salesperson consultation in the pre-decision stage of organizational purchasing

2020 ◽  
Vol 85 ◽  
pp. 152-166
Author(s):  
Leff Bonney ◽  
Bryan Hochstein ◽  
Brett Christenson ◽  
Ellis Chefor
Keyword(s):  
Decision Stage ◽  
Organizational Purchasing

The Decision Stage and Res Judicata

1965 ◽  
pp. 241-255
Author(s):  
Mauro Cappelletti ◽  
Joseph M. Perillo
Keyword(s):  
Decision Stage ◽  
Res Judicata

Some Causes of Automobile-Motorcycle Collisions

1989 ◽  
Vol 33 (15) ◽  
pp. 910-914 ◽  
Author(s):  
Gabriele Wulf ◽  
P. A. Hancock ◽  
Mansour Rahimi
Keyword(s):  
Information Processing ◽  
Empirical Research ◽  
Motor Vehicle ◽  
Motor Vehicle Accidents ◽  
Decision Stage ◽  
Vehicle Accidents

Motorcycles are overrepresented in fatal motor-vehicle accidents. In the attempt to reduce the frequency of automobile-motorcycle collisions, numerous studies have manipulated motorcycle and motoryclist characteristics to enhance conspicuity. In this paper, we review of studies that have examined the effectiveness of these measures. Furthermore, we identify factors yet to be considered in the empirical research in this area that may contribute to collisions between cars and motorcycles. These include information-processing failures at the identification and decision stage, as well as relatively stable and volatile factors potentially responsible for different information-processing failures.

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