A Reference Recursive Recipe for Tuning the Statistics of the Kalman Filter

The philosophy and the historical development of Kalman filter from ancient times to the present is followed by the connection between randomness, probability, statistics, random process, estimation theory, and the Kalman filter. A brief derivation of the filter is followed by its appreciation, aesthetics, beauty, truth, perspectives, competence, and variants. The menacing and notorious problem of specifying the filter initial state, measurement, and process noise covariances and the unknown parameters remains in the filter even after more than five decades of enormous applications in science and technology. Manual approaches are not general and the adaptive ones are difficult. The proposed reference recursive recipe (RRR) is simple and general. The initial state covariance is the probability matching prior between the Frequentist approach via optimization and the Bayesian filtering. The filter updates the above statistics after every pass through the data to reach statistical equilibrium within a few passes without any optimization. Further many proposed cost functions help to compare the present and earlier approaches. The efficacy of the present RRR is demonstrated by its application to a simulated spring, mass, and damper system and a real airplane flight data having a larger number of unknown parameters and statistics

Tuning of the Kalman Filter Using Constant Gains

For designing an optimal Kalman filter, it is necessary to specify the statistics, namely the initial state, its covariance and the process and measurement noise covariances. These can be chosen by minimising some suitable cost function J . This has been very difficult till recently when a near optimal Recurrence Reference Recipe (RRR) was proposed without any optimisation but only filtering. In many filter applications after the initial transients, the gain matrix K tends to a constant during the steady state, which points to design the filter based on constant gains alone. Such a constant gain Kalman filter (CGKF) can be designed by minimising any suitable cost function. Since there are no covariances in CGKF, only the state equations need to be propagated and updated at a measurement, thus enormously reducing the computational load. Though CGKF results may not be too close to those of RRR, they are acceptable. It accepts extremely simple models and the gains are robust in handling similar scenarios. In this chapter, we provide examples of applying the CGKF by ancient Indian astronomers, parameter estimation of spring, mass and damper system, airplane real flight test data, ballistic rocket, re-entry of space object and the evolution of space debris

Exploring the international connectivity of Chinese inventors in the pharmaceutical industry

This paper explores the integration of emerging countries into the global system of innovation, as a channel for their technological catch-up. Using data on the innovative activity in the Chinese pharmaceutical industry, we analyze the geographic dispersion of inventor networks linked to China, as a function of the characteristics of the innovative actors that coordinate their inventive work

Knowledge connectivity in an adverse context: global value chains and Pakistani offshore service providers

This paper contributes to theory building efforts around the concept of knowledge connectivity and its relevance in buyer-supplier relationships in global value chains. We use the Pakistani IT industry as our study context. Pakistan suffered a significant adverse perception bias following terror attacks in 2008-09. We based our illustration on the experiences of 12 Pakistani offshore service providers (OSPs) who succeeded in offsetting the negative implications of the country’s adverse political environment. The case firms link into two distinct value chain configurations. In each configuration, we observe a distinct course of strategic action, which we term step-up and break-out, respectively. While these observations emerged from the Pakistani context, the implications of the resulting dynamic framework for theory and practice go beyond this particular adverse country setting

The future of global strategy

Research Summary: Global strategy, that is, the analysis of strategy in an international context, has co-evolved with the dramatic changes in the global economy in the 21st century. Research advances have enabled a more sophisticated understanding of how firms develop strategies in an increasingly turbulent global environment in which societal expectations, technological advances, and political decisions are all in a state of continuous change. In this article, we reflect and provide suggestions for how the field may evolve on five key themes of global strategy: cooperation, coordination, governance, politics, and innovation. We also outline suggestions for future research on global issues that are gaining increasing centrality in business decisions: climate change, artificial intelligence, and geopolitics. Managerial Summary: The study of how the context affects firms' strategies has changed with the transformation of the world in the 21st century. Research has provided a better understanding of how managers create and implement strategies in response to changes in societal expectations, technological advances, and political decisions. In this article, we reflect and provide suggestions for future studies on five key themes of global strategy: cooperation, coordination, governance, politics, and innovation in multinationals. We also outline suggestions for analyzing the increasingly important grand challenges that affect business decisions: climate change, artificial intelligence, and geopolitics

What lies between market and hierarchy? Insights from internalization theory and global value chain theory

In this paper, we suggest that internalization theory might be extended by incorporating complementary insights from GVC theory. More specifically, we argue that internalization theory can explain why lead firms might wish to externalize selected activities, but that it is largely silent on the mechanisms by which those lead firms might exercise control over the resultant externalized relationships with their GVC partners. We advance an explanation linking the choice of control mechanism to two factors: power asymmetries between the lead firms and their GVC partners, and the degree of codifiability of the information to be exchanged in the relationship