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Introduction to Algorithms and Data Structures
Published in Sriraman Sridharan, R. Balakrishnan, Foundations of Discrete Mathematics with Algorithms and Programming, 2019
Sriraman Sridharan, R. Balakrishnan
Similarly, in programming, a function which calls (invokes) itself either directly or indirectly is referred to as a recursive function. A function F invoking itself, that is, there is a statement in the body of the function F referring to itself, is called a direct recursion. This means that in graphical terminology, we have a loop around the vertex F. On the other hand, if the function F invokes the function G, which in turn invokes the function H, which again calls the function F, then such a situation is referred to as an indirect recursion. This means that we have a circuit of length three (F, G, H, F). Each arc is interpreted as an invocation. Recursion allows us to write compact and concise programs.
Introduction to LabVIEW
Published in Rick Bitter, Taqi Mohiuddin, Matt Nawrocki, LabVIEW™ Advanced Programming Techniques, 2017
Rick Bitter, Taqi Mohiuddin, Matt Nawrocki
Shift registers are the only mechanisms available to perform recursive operations in LabVIEW. Recursion is the ability for a function to call itself during execution, and it has frustrated thousands of students learning C and C++. The good news for LabVIEW programmers is that VIs cannot wrap back onto themselves in a wire diagram. There are times when a recursive operation is the best way to solve a problem, and using shift registers simulate recursion. Although not truly recursive, access to the last iterations can be used to perform these ever-popular algorithms in LabVIEW. It is not possible for LabVIEW to overrun a call stack with shift registers, which is very possible with recursive functions in C. One of the problems with recursion is that if exit criteria are not correct, the function will not be able to stop calling itself and will crash the application. Memory usage is also a bit more efficient for shift registers because there is not as much call stack abuse.
Hello World!
Published in Syed R. Rizvi, Microcontroller Programming, 2016
The Fibonacci series can be generated using both iteration and recursion. They both are based on a control structure: iteration uses a repetition structure; recursion uses a selection structure. Both iteration and recursion involve repetition: Iteration explicitly uses a repetition structure; recursion achieves repetition through repeated subroutine calls. Although this series can be generated by recursion, but because recursion is expensive for the processor and memory space assignment due to the overhead of subroutine calls, we will use an iterative approach to create the first 10 elements of this series. The program flow is shown in Figure 7.23.
Impact of investor sentiment on mutual fund risk taking and performance: evidence from China
Published in Enterprise Information Systems, 2020
Jian Wang, Xiaoting Wang, Jun Yang, Xintian Zhuang
As illustrated in Figure 1, there exist dynamic interactions between investors and managers in mutual fund industry. Investors’ investing decision is often driven by market sentiment, which leads to the delegation of their money to fund managers. Eventually, fund investment strategies (style) and performance (success) would affect and feed investor sentiment. This is a circular and recursive process. The objective of this study is to present empirical evidence how investor sentiment affects mutual fund strategy and performance so as to provide guidance on incorporating investor sentiment into investment enterprise information systems.
Public engagement in contested political contexts: reflections on the role of recursive reflexivity in responsible innovation
Published in Journal of Responsible Innovation, 2020
This issue explores the imperatives and limitations of RI in light of reflections on asymmetries, in what we are calling the ‘recursive reflexivity’ of responsible innovation. While the well-known ‘AIRR’ framework of anticipation, inclusion, responsiveness, and reflexivity (Stilgoe, Owen, and Macnaghten 2013) remains a key approach to RI, these very same dimensions of praxis can be continually taken up – as RI scholars have already done (De Hoop, Pols, and Romijn 2016; Brand and Blok 2019; Hartley et al. 2019)–to interrogate RI on both theoretical and pragmatic levels. Stilgoe et al. define reflexivity at the institutional level as ‘ … holding a mirror up to one’s own activities, commitments and assumptions, being aware of the limits of knowledge and being mindful that a particular framing of an issue may not be universally held’ (2013, 1570). While the special issue contributors speak to cultivating reflexivity within contexts of science and technology governance–from the laboratory to research funders and other governance institutions–their conversations implicitly highlight the ways that STS and RI scholars engaging the work of responsible innovation are operating within these contexts, not outside them. That is, reflexivity is not only to be cultivated among scientists, policymakers, and the stakeholders explicitly shaping science and innovation, but in the STS/RI researcher as well. Recursion in the context of computer programming, from which we are borrowing, generally refers to an instance in which a function–which contains steps to execute–calls itself. Here, by metaphor, we posit that RI calls itself. Anticipation, inclusion, responsiveness, reflexivity and other dimensions (Fraaije and Flipse 2020) and approaches (Pellé 2016) to RI are not just elements of a heuristic framework for cultivating responsible innovation but are principles for reflexively examining RI practices themselves and attendant questions concerning democratic engagement with science and technology.