This article derives a generalized algorithm for duration and convexity of option embedded bonds that provides a convenient way of estimating the dollar value of 1 basis point change in yield known as DV01, an importa...
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This article derives a generalized algorithm for duration and convexity of option embedded bonds that provides a convenient way of estimating the dollar value of 1 basis point change in yield known as DV01, an important metric in the bond market. As delta approaches 1, duration of callable bonds approaches zero once the bond is called. However, when the delta is zero, the short call is worthless and duration of callable will be equal to that of a straight bond. On the other hand, the convexity of a callable bond follows the same behaviour when the delta is 1 as shown in Dunetz and Mahoney (1988) as well as in Mehran and Homaifar's (1993) derivations. However, in the case when delta is zero, the convexity of a callable bond approaches zero as well, which is in stark contrast to the non-zero convexity derived in Dunetz and Mahoney's paper. Our generalized algorithm shows that duration and convexity nearly symmetrically underestimate (overestimate) the actual price change by 11/10 basis points for +/- 100 basis points change in yield. Furthermore, our algorithm reduces to that of MH for convertible bonds assuming the convertible bond is not callable.
Pulse-like signals are ubiquitous in the field of single molecule analysis, e.g., electrical or optical pulses caused by analyte translocations in nanopores. The primary challenge in processing pulse-like signals is t...
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Pulse-like signals are ubiquitous in the field of single molecule analysis, e.g., electrical or optical pulses caused by analyte translocations in nanopores. The primary challenge in processing pulse-like signals is to capture the pulses in noisy backgrounds, but current methods are subjectively based on a user-defined threshold for pulse recognition. Here, we propose a generalized machine-learning based method, named pulse detection transformer (PETR), for pulse detection. PETR determines the start and end time points of individual pulses, thereby singling out pulse segments in a time-sequential trace. It is objective without needing to specify any threshold. It provides a generalized interface for downstream algorithms for specific application scenarios. PETR is validated using both simulated and experimental nanopore translocation data. It returns a competitive performance in detecting pulses through assessing them with several standard metrics. Finally, the generalization nature of the PETR output is demonstrated using two representative algorithms for feature extraction.
generalized algorithm for determining the I-pv-V-pv and P-pv-V-pv curves at given insolation and temperature of solar photovoltaic (SPV) array, under partial shadow conditions is proposed in this paper. The algorithm ...
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ISBN:
(纸本)9781665459303
generalized algorithm for determining the I-pv-V-pv and P-pv-V-pv curves at given insolation and temperature of solar photovoltaic (SPV) array, under partial shadow conditions is proposed in this paper. The algorithm is proficient of developing the characteristics of SPV array of any configuration with any kind of shadow pattern. Individual module specifications are also inputted. A MATLAB code is developed for the algorithm and I-pv-V-pv and P-pv-V-pv curves of a sample system of [4*3] PV array are identified for ten shadow patterns. For each shadow pattern values of Vmp and Pmp (voltage and peak power) are also identified using the algorithm, which are further required for peak power point tracking (PPPT).
Path finding is an important problem in robot design and automation that requires quick error-free solutions that rely on external environment. Automated mobile robotic systems employ various techniques to determine t...
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ISBN:
(纸本)9781538674765
Path finding is an important problem in robot design and automation that requires quick error-free solutions that rely on external environment. Automated mobile robotic systems employ various techniques to determine the path that the robot needs to follow to reach the destination to perform its function. Path finding problems can utilize various algorithms to solve the problem. Sensor data can be used as a reference to determine the path to be followed from the start point to the destination. However, this technique is highly localized and does not provide the ability to make decisions by taking global constraints or conditions into consideration. Image processing techniques are employed extensively to provide a solution based on global conditions. The proposed method involves use of image processing to process the acquired image of the maze from a mounted camera system. The processing steps are used to provide steps which the robot can follow to reach from its current position to the final position. This project implements a universal algorithm to allow the robot to maneuver autonomously.
Traditionally, the convergence rate of the sliding variable given by a discrete reaching law has been fixed in nature. This paper presents a generalized algorithm for discrete time sliding mode control systems which o...
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Traditionally, the convergence rate of the sliding variable given by a discrete reaching law has been fixed in nature. This paper presents a generalized algorithm for discrete time sliding mode control systems which offers a flexible convergence rate for the sliding variable. For analysis, we use the recently developed band approach method which gives us the values of the parameters in the algorithm for the desired convergence to take place, once the ultimate band is chosen appropriately. (C) 2015 Elsevier Ltd. All rights reserved.
The paper presents a generalized algorithm for the reaching and boundedness of the sliding variable in case of discrete time sliding mode control systems. The algorithm is general as it not only comprises functions in...
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The paper presents a generalized algorithm for the reaching and boundedness of the sliding variable in case of discrete time sliding mode control systems. The algorithm is general as it not only comprises functions in the sliding variable, but also functions in other variables, which are known. With the help of the proposed generalized reaching law, an important problem of a reaching law with uncertainty bounded by known functions is studied. The convergence of the sliding variable to an ultimate bounding function in presence of such an uncertainty is shown by the band approach method. This is achieved by appropriately selecting the functions in the proposed generalized reaching law. (C) 2014 Elsevier Ltd. All rights reserved.
In this paper, we propose a class of generalized flocking algorithms based on the Olfati-Saber's results for self-driving multi-agent networks by introducing some metric weighting matrix and leader-agent-related n...
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ISBN:
(纸本)9781509035502
In this paper, we propose a class of generalized flocking algorithms based on the Olfati-Saber's results for self-driving multi-agent networks by introducing some metric weighting matrix and leader-agent-related navigation-weighting coefficients, in which the multi-agents are also driven by distributed continuous-time control algorithms that are defined merely by local position and velocity measurements of neighboring multi-agents as usual. It is shown that the concerned multi-agent systems eventually run into what we call the generalized α-lattice flocking by means of the generalized algorithms, while flocking lattice geometries such as direction variation and lattice deformation (say, shrinkage and enlargement) can be achieved by choosing the weighting matrix and the leader agent coefficients. In the process of flocking, the whole multi-agent system satisfies the Reynold's principles of flocking aggregation, collision avoidance and velocity matching, while possible inter-agent collision is also verified by means of the variation-of-constants formula when initially the agents are aggregative too densely.
In order for robots to interact safely and intelligently with their environment they must be able to reliably estimate and localize external contacts. This paper introduces CPF, the Contact Particle Filter, which is a...
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ISBN:
(纸本)9781509037636
In order for robots to interact safely and intelligently with their environment they must be able to reliably estimate and localize external contacts. This paper introduces CPF, the Contact Particle Filter, which is a general algorithm for detecting and localizing external contacts on rigid body robots without the need for external sensing. CPF finds external contact points that best explain the observed external joint torque, and returns sensible estimates even when the external torque measurement is corrupted with noise. We demonstrate the capability of the CPF to track multiple external contacts on a simulated Atlas robot, and compare our work to existing approaches.
In recent years, researchers come up with lots of path following algorithms. One of their basic assumptions is that the robot's initial position is a single certain point. Actually, as robots rely on sensor data t...
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ISBN:
(纸本)9781479974894
In recent years, researchers come up with lots of path following algorithms. One of their basic assumptions is that the robot's initial position is a single certain point. Actually, as robots rely on sensor data to locate by Kalman filter or Partical filter, it outputs a probability distribution. In this paper, F* describes a new path following algorithm with the robot's initial position is uncertain. It depends on Monte Carlo method and A* algorithm. Some important concepts are introduced and pseudo code is given to show how it works. Experiment results show that it is more effective than general algorithm.
In this study the scheduling supply chain models combination in terms of optimal program control is considered. The SC schedule execution problem is formulated. It is consist of the problem of optimal program control ...
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ISBN:
(纸本)9781467376983
In this study the scheduling supply chain models combination in terms of optimal program control is considered. The SC schedule execution problem is formulated. It is consist of the problem of optimal program control and the problem of positional control. Then for solving considered problem we propose to use mathematical methods of optimal control theory and linear programming, adaptive method. The generalized algorithm is represented and verified on numerical examples.
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