Remarks on the Solution of the Position Dependent Mass (PDM) Schr\"odinger Equation

An approximate method is proposed to solve position dependent mass Schr\"odinger equation. The procedure suggested here leads to the solution of the PDM Schr\"odinger equation without transforming the potential function to the mass space or vice verse. The method based on asymptotic Taylor expansion of the function, produces an approximate analytical expression for eigenfunction and numerical results for eigenvalues of the PDM Schr\"odinger equation. The results show that PDM and constant mass Schr\"odinger equations are not isospectral. The calculations are carried out with the aid of a computer system of symbolic or numerical calculation by constructing a simple algorithm

On the Structure of Equilibrium Strategies in Dynamic Gaussian Signaling Games

This paper analyzes a finite horizon dynamic signaling game motivated by the well-known strategic information transmission problems in economics. The mathematical model involves information transmission between two agents, a sender who observes two Gaussian processes, state and bias, and a receiver who takes an action based on the received message from the sender. The players incur quadratic instantaneous costs as functions of the state, bias and action variables. Our particular focus is on the Stackelberg equilibrium, which corresponds to information disclosure and Bayesian persuasion problems in economics. Prior work solved the static game, and showed that the Stackelberg equilibrium is achieved by pure strategies that are linear functions of the state and the bias variables. The main focus of this work is on the dynamic (multi-stage) setting, where we show that the existence of a pure strategy Stackelberg equilibrium, within the set of linear strategies, depends on the problem parameters. Surprisingly, for most problem parameters, a pure linear strategy does not achieve the Stackelberg equilibrium which implies the existence of a trade-off between exploiting and revealing information, which was also encountered in several other asymmetric information games.Comment: will appear in IEEE Multi-Conference on Systems and Control 201

Single Bit and Reduced Dimension Diffusion Strategies Over Distributed Networks

We introduce novel diffusion based adaptive estimation strategies for distributed networks that have significantly less communication load and achieve comparable performance to the full information exchange configurations. After local estimates of the desired data is produced in each node, a single bit of information (or a reduced dimensional data vector) is generated using certain random projections of the local estimates. This newly generated data is diffused and then used in neighboring nodes to recover the original full information. We provide the complete state-space description and the mean stability analysis of our algorithms.Comment: Submitted to the IEEE Signal Processing Letter

Compressive Diffusion Strategies Over Distributed Networks for Reduced Communication Load

We study the compressive diffusion strategies over distributed networks based on the diffusion implementation and adaptive extraction of the information from the compressed diffusion data. We demonstrate that one can achieve a comparable performance with the full information exchange configurations, even if the diffused information is compressed into a scalar or a single bit. To this end, we provide a complete performance analysis for the compressive diffusion strategies. We analyze the transient, steady-state and tracking performance of the configurations in which the diffused data is compressed into a scalar or a single-bit. We propose a new adaptive combination method improving the convergence performance of the compressive diffusion strategies further. In the new method, we introduce one more freedom-of-dimension in the combination matrix and adapt it by using the conventional mixture approach in order to enhance the convergence performance for any possible combination rule used for the full diffusion configuration. We demonstrate that our theoretical analysis closely follow the ensemble averaged results in our simulations. We provide numerical examples showing the improved convergence performance with the new adaptive combination method.Comment: Submitted to IEEE Transactions on Signal Processin

IMPACT ASSESSMENT ON MILK INCENTIVE POLICIES IN TURKEY: ANTALYA PROVINCE CASE

Agricultural policy instruments are implementing in different ways among all agricultural based activities. These instruments have been performed for livestock including dairy cattle and milk for many years in Turkey. Until the year 1950, agricultural support system was organized according to genetically improvement, animal illnesses and veterinary services. Nowadays, agricultural support composition has changed. Milk incentive premium is one of the supports given to producers to achieve high quality level for milk. The idea behind this premium was to provide well organized milk distribution channel from producers to modern enterprises. In this study, producers who receive milk incentive premium were chosen for face to face survey in Antalya province. It was examined from the study if premium system is accomplished through the idea. The secondary outcomes of the research were to determine the influence of the premium on producers attitudes, income level, product quantity, as well as membership tendency for cooperatives or unions.milk incentive premium, milk marketing, producer surplus, Antalya, Agricultural and Food Policy, Livestock Production/Industries,