Soft computing, intelligent robotics and control are in the core
interest of contemporary engineering. Essential characteristics of
soft computing methods are the ability to handle vague information,
to apply human-like reasoning, their learning capability and ease
of application. Soft computing techniques are widely applied in the
control of dynamic systems, including mobile robots. The present
volume is a collection of 20 chapters written by respectable
experts of the fields, addressing various theoretical and practical
aspects in soft computing, intelligent robotics and control.
The first part of the book concerns with issues of intelligent
robotics, including robust xed point transformation design,
experimental verification of the input-output feedback
linearization of differentially driven mobile robot and applying
kinematic synthesis to micro electro-mechanical systems design.
The second part of the book is devoted to fundamental aspects of
soft computing. This includes practical aspects of fuzzy rule
interpolation, subjective weights based meta learning in multi
criteria decision making, swarm-based heuristics for an area
exploration and knowledge driven adaptive product
representations.
The last part addresses different problems, issues and methods
of applied mathematics. This includes perturbation estimates for
invariant subspaces of Hessenberg matrices, uncertainty and
nonlinearity modelling by probabilistic metric spaces and
comparison and visualization of the DNA of six primates.
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