Inflation Dynamics’ Micro Foundations: How Important is Imperfect Competition Really?

This paper analyzes price formation and dynamics according to the industry structure. It divides manufacturing industries of Mexico into two groups: perfectly and imperfectly competitive. The results show that imperfectly competitive industries predominate. Then this classification is used to build consumer price sub indexes for the goods of both sectors. These sub indexes’ inflation dynamics indicate that the exchange rate pass-through in the perfectly competitive sector is significantly higher than in the imperfectly competitive sector, while wage pass-through only affects the imperfectly competitive sector. Also, that inflation inertia is lower in the former than in the latter; adding up in more volatility of the perfectly competitive inflation rate. For policy makers an interesting feature of the perfectly competitive price index is that the evidence suggests that its variations precede those of the imperfectly competitive price index. For economic theorists these features validate recent macroeconomic models with heterogeneous price setting behaviorPanzar-Rosse, Industry Structure, Inflation, Price Dynamics, Price Indexes

A Finite Element Method Approach for Trajectory Generation via Time-Optimal Control and Model Predictive Control Tracking

In this paper a framework for solving the time optimal control (TOC) using Galerkin's Weighted Residuals Method (GWRM) and Sequential Convex Programming (SCP) is proposed. The proposed method solves the two-point boundary value problem, avoiding the use of shooting methods that rely heavily on the appropriate initialization of the adjoint state and optimal time. Since TOC yields an open-loop controller, a Model Predictive Control (MPC) scheme is employed to track both the optimal trajectory and controller, allowing the system to reject disturbances. The approach is validated using the Dubins' car dynamics for optimal time trajectory generation

Algorithmic Minimization of Non-zero Entries in 0,1-Matrices

In this paper we present algorithms which work on pairs of 0,1- matrices which multiply again a matrix of zero and one entries. When applied over a pair, the algorithms change the number of non-zero entries present in the matrices, meanwhile their product remains unchanged. We establish the conditions under which the number of 1s decreases. We recursively define as well pairs of matrices which product is a specific matrix and such that by applying on them these algorithms, we minimize the total number of non-zero entries present in both matrices. These matrices may be interpreted as solutions for a well known information retrieval problem, and in this case the number of 1 entries represent the complexity of the retrieve and information update operations

Una lengua popular como un río vivo

Libro reseñado: Sofoco. Laura Ortiz Gómez. Laguna Libros, Bogotá, 2021, 120 pp

Voces demasiado seguras, lenguas insuficientes

Libro reseñado: Toda esa suciedad. Juan Diego Serrano. Universidad Industrial de Santander, Bucaramanga, 2019, 214 pp

Voces demasiado seguras, lenguas insuficientes

Libro reseñado: Toda esa suciedad. Juan Diego Serrano. Universidad Industrial de Santander, Bucaramanga, 2019, 214 pp

Data Reduction in the String Space for Efficient kNN Classification through Space Partitioning

Within the Pattern Recognition field, two representations are generally considered for encoding the data: statistical codifications, which describe elements as feature vectors, and structural representations, which encode elements as high-level symbolic data structures such as strings, trees or graphs. While the vast majority of classifiers are capable of addressing statistical spaces, only some particular methods are suitable for structural representations. The kNN classifier constitutes one of the scarce examples of algorithms capable of tackling both statistical and structural spaces. This method is based on the computation of the dissimilarity between all the samples of the set, which is the main reason for its high versatility, but in turn, for its low efficiency as well. Prototype Generation is one of the possibilities for palliating this issue. These mechanisms generate a reduced version of the initial dataset by performing data transformation and aggregation processes on the initial collection. Nevertheless, these generation processes are quite dependent on the data representation considered, being not generally well defined for structural data. In this work we present the adaptation of the generation-based reduction algorithm Reduction through Homogeneous Clusters to the case of string data. This algorithm performs the reduction by partitioning the space into class-homogeneous clusters for then generating a representative prototype as the median value of each group. Thus, the main issue to tackle is the retrieval of the median element of a set of strings. Our comprehensive experimentation comparatively assesses the performance of this algorithm in both the statistical and the string-based spaces. Results prove the relevance of our approach by showing a competitive compromise between classification rate and data reduction.This research work was partially funded by “Programa I+D+i de la Generalitat Valenciana” through grant ACIF/2019/ 042 and the Spanish Ministry through HISPAMUS project TIN2017-86576-R, partially funded by the EU

El presente

Libro reseñado: Primera persona. Margarita García Robayo. Laguna Libros, Bogotá, 2018, 116 pp

Three Realizations and Comparison of Hardware for Piezoresistive Tactile Sensors

Tactile sensors are basically arrays of force sensors that are intended to emulate the skin in applications such as assistive robotics. Local electronics are usually implemented to reduce errors and interference caused by long wires. Realizations based on standard microcontrollers, Programmable Systems on Chip (PSoCs) and Field Programmable Gate Arrays (FPGAs) have been proposed by the authors for the case of piezoresistive tactile sensors. The solution employing FPGAs is especially relevant since their performance is closer to that of Application Specific Integrated Circuits (ASICs) than that of the other devices. This paper presents an implementation of such an idea for a specific sensor. For the purpose of comparison, the circuitry based on the other devices is also made for the same sensor. This paper discusses the implementation issues, provides details regarding the design of the hardware based on the three devices and compares them.This work has been partially funded by the Spanish Government under contracts TEC2006-12376 and TEC2009-14446

General Formula for Event-Based Stabilization of Nonlinear Systems with Delays in the State

International audienceIn this chapter, a universal formula is proposed for event-based stabilization of nonlinear systems affine in the control and with delays in the state. The feedback is derived from the seminal law proposed by E. Sontag (1989) and then extended to event-based control of affine nonlinear undelayed systems. Under the assumption of the existence of a control Lyapunov-Krasovskii functional (CLKF), the proposal enables smooth (except at the origin) asymptotic stabilization while ensuring that the sampling intervals do not contract to zero. Global asymptotic stability is obtained under the small control property assumption. Moreover, the control can be proved to be smooth anywhere under certain conditions. Simulation results highlight the ability of the proposed formula. The particular linear case is also discussed