scholarly journals A CLOSED-FORM SOLUTION FOR THE HEALTH CAPITAL MODEL

2015 ◽  
Vol 81 (3) ◽  
pp. 301-316 ◽  
Author(s):  
Holger Strulik
Keyword(s):  
Closed Form ◽  
Capital Stock ◽  
Closed Form Solution ◽  
Optimal Solution ◽  
Form Solution ◽  
Investment Model ◽  
Eternal Life ◽  
Health Capital ◽  
Comparative Dynamics ◽  
Health Demand

Abstract:This paper provides a closed-form solution for the health capital model of health demand. The results are exploited in order to prove analytically the comparative dynamics of the model. Results are derived for the so-called pure investment model, the pure consumption model and a combination of both types of models. Given the plausible assumptions that (i) health declines with age and that (ii) the health capital stock at death is lower than the health capital stock needed for eternal life, it is shown that the optimal solution implies eternal life.

scholarly journals The Chow-Lin method extended to dynamic models with autocorrelated residuals

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Aurélien Poissonnier
Keyword(s):  
Closed Form ◽  
Capital Stock ◽  
High Frequency ◽  
Dynamic Models ◽  
Closed Form Solution ◽  
Dynamic Structure ◽  
Form Solution ◽  
Static Models ◽  
Temporal Disaggregation ◽  
Communication Equipment

AbstractI provide a closed-form solution to temporal disaggregation or interpolation models which is both general in terms of dynamic structure of the model (lags of the high-frequency variable) and flexible in terms of autocorrelation of its residual. As for static models, I show that assuming autocorrelated residuals in dynamic models is practically convenient. To illustrate the potential of the solution proposed, I provide an example for quarterly non-financial corporations’ capital stock in computers and communication equipment.

scholarly journals Similarity Measure Learning in Closed-Form Solution for Image Classification

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Jing Chen ◽  
Yuan Yan Tang ◽  
C. L. Philip Chen ◽  
Bin Fang ◽  
Zhaowei Shang ◽  
...  
Keyword(s):  
Closed Form ◽  
Similarity Measure ◽  
Dimensional Space ◽  
Closed Form Solution ◽  
Optimal Solution ◽  
Research Problem ◽  
Form Solution ◽  
Similarity Learning ◽  
Learning Tasks ◽  
Active Research

Adopting a measure is essential in many multimedia applications. Recently, distance learning is becoming an active research problem. In fact, the distance is the natural measure for dissimilarity. Generally, a pairwise relationship between two objects in learning tasks includes two aspects: similarity and dissimilarity. The similarity measure provides different information for pairwise relationships. However, similarity learning has been paid less attention in learning problems. In this work, firstly, we propose a general framework for similarity measure learning (SML). Additionally, we define a generalized type of correlation as a similarity measure. By a set of parameters, generalized correlation provides flexibility for learning tasks. Based on this similarity measure, we present a specific algorithm under the SML framework, called correlation similarity measure learning (CSML), to learn a parameterized similarity measure over input space. A nonlinear extension version of CSML, kernel CSML, is also proposed. Particularly, we give a closed-form solution avoiding iterative search for a local optimal solution in the high-dimensional space as the previous work did. Finally, classification experiments have been performed on face databases and a handwritten digits database to demonstrate the efficiency and reliability of CSML and KCSML.

On a Closed-Form Solution of Prandtl's System of Equations

2013 ◽  
Vol 40 (2) ◽  
pp. 106-114
Author(s):  
J. Venetis ◽  
Aimilios (Preferred name Emilios) Sideridis
Keyword(s):  
Closed Form ◽  
Closed Form Solution ◽  
Form Solution ◽  
System Of Equations

Capacity Analysis for Correlated Multi-Hop MIMO Channels under Colored Noise

2015 ◽  
Vol 1 ◽  
pp. 41
Author(s):  
Nguyen N. Tran ◽  
Ha X. Nguyen
Keyword(s):  
Computational Complexity ◽  
Mutual Information ◽  
Closed Form Solution ◽  
Optimal Solution ◽  
Form Solution ◽  
Maximization Problem ◽  
Capacity Analysis ◽  
Mimo Channels ◽  
Average Mutual Information ◽  
Channel Output

A capacity analysis for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels is presented in this paper. The channel at each hop is spatially correlated, the source symbols are mutually correlated, and the additive Gaussian noises are colored. First, by invoking Karush-Kuhn-Tucker condition for the optimality of convex programming, we derive the optimal source symbol covariance for the maximum mutual information between the channel input and the channel output when having the full knowledge of channel at the transmitter. Secondly, we formulate the average mutual information maximization problem when having only the channel statistics at the transmitter. Since this problem is almost impossible to be solved analytically, the numerical interior-point-method is employed to obtain the optimal solution. Furthermore, to reduce the computational complexity, an asymptotic closed-form solution is derived by maximizing an upper bound of the objective function. Simulation results show that the average mutual information obtained by the asymptotic design is very closed to that obtained by the optimal design, while saving a huge computational complexity.

scholarly journals A Closed-Form Solution to Planar Feature-Based Registration of LiDAR Point Clouds

2021 ◽  
Vol 10 (7) ◽  
pp. 435
Author(s):  
Yongbo Wang ◽  
Nanshan Zheng ◽  
Zhengfu Bian
Keyword(s):  
Closed Form ◽  
Closed Form Solution ◽  
Simulated Data ◽  
Real Data ◽  
Point Clouds ◽  
Form Solution ◽  
Spatial Transformation ◽  
Dual Quaternions ◽  
Feature Based ◽  
Planar Feature

Since pairwise registration is a necessary step for the seamless fusion of point clouds from neighboring stations, a closed-form solution to planar feature-based registration of LiDAR (Light Detection and Ranging) point clouds is proposed in this paper. Based on the Plücker coordinate-based representation of linear features in three-dimensional space, a quad tuple-based representation of planar features is introduced, which makes it possible to directly determine the difference between any two planar features. Dual quaternions are employed to represent spatial transformation and operations between dual quaternions and the quad tuple-based representation of planar features are given, with which an error norm is constructed. Based on L2-norm-minimization, detailed derivations of the proposed solution are explained step by step. Two experiments were designed in which simulated data and real data were both used to verify the correctness and the feasibility of the proposed solution. With the simulated data, the calculated registration results were consistent with the pre-established parameters, which verifies the correctness of the presented solution. With the real data, the calculated registration results were consistent with the results calculated by iterative methods. Conclusions can be drawn from the two experiments: (1) The proposed solution does not require any initial estimates of the unknown parameters in advance, which assures the stability and robustness of the solution; (2) Using dual quaternions to represent spatial transformation greatly reduces the additional constraints in the estimation process.

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