Space and Time Complexities, Threshold Selection, Adaptation

  • Le Yi Wang
  • G. George Yin
  • Ji-Feng Zhang
  • Yanlong Zhao
Part of the Systems & Control: Foundations & Applications book series (SCFA)


The number m0 of thresholds is a measure of space complexity, whereas the observation length N is a measure of time complexity that quantifies how fast uncertainty can be reduced. The significance of understanding space and time complexities can be illustrated by the following example. For computer information processing of a continuous-time system, its output must be sampled (e.g., with a sampling rate N Hz) and quantized (e.g., with a precision word-length of B bits). Consequently, its output observations carry the data-flow rate of NB bits per second (bps). For instance, for 8- bit precision and a 10-KHz sampling rate, an 80K-bps bandwidth of data transmission resource is required. In a sensor network in which a large number of sensors must communicate within the network, such resource demand is overwhelming especially when wireless communications of data are involved.


Time Complexity Space Complexity Optimal Threshold Sensor Threshold Threshold Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Le Yi Wang
    • 1
  • G. George Yin
    • 2
  • Ji-Feng Zhang
    • 3
  • Yanlong Zhao
    • 3
  1. 1.Department of Electrical and Computer EngineeringWayne State UniversityDetroitUSA
  2. 2.Department of MathematicsWayne State UniversityDetroitUSA
  3. 3.Key Laboratory of Systems and Control, Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijingChina

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