平常
发表于 2025-3-23 12:07:24
Probability Theory,Probability theory deals with the study of events whose precise occurrence cannot be predicted in advance. These kind of events are also termed as random events. For example, a toss of a coin, the result may be either HEAD or TAIL. The result cannot be predicted, hence the event—tossing a coin—is an example of random event.
exorbitant
发表于 2025-3-23 15:41:51
Stochastic Processes and Models,The word “stochastic” is of Greek origin. In seventeenth century English, the word “stochastic” had the meaning “to conjecture, to aim at mark”. It is not quite clear how it acquired the meaning it has today of “pertaining to chance”.
corn732
发表于 2025-3-23 18:30:11
Dependability Models of Computer-Based Systems,Computer-based reactive systems which interact with their environment in a timely manner are called . systems. The main characteristics of real-time systems which distinguishes them from others is that the correctness (or healthiness) of the system depends
羞辱
发表于 2025-3-24 00:53:40
Network Technologies for Real-Time Systems,The purpose of this chapter is to introduce basic term and concepts of network technology. Main emphasis of is on schedulers and real-time analysis of these networks. Networks used in critical applications, such as, CAN and MIL-STD-1553B are discussed in detail.
整理
发表于 2025-3-24 03:58:07
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共和国
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inspiration
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EPT
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inculpate
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N. Nakanishi,K. Ozawa,S. Yamadag, with finite steady-state distribution) is tracked. By this method, the problem of computing the response time distribution of the tagged customer is transformed into time to absorption distribution of a finite-state, continuous time Markov chain (CTMC), conditioned on the state of the system upon
拔出
发表于 2025-3-25 02:51:14
Dental pulp fibroblasts in culturent on healthiness of its constituent components and error free operation of communication links. Ensuring timeliness is dependent upon the delay offered at various stages of node and communication links of the system. So, reliability of a real-time system can be defined as a probabilistic measure of