Sinopsis
Engineering disciplines are those fields of research and development that attempt to create products and systems operating in, and dealing with, the real world. The number of disciplines is large, as is the range of scales that they typically operate in: from the very small scale of nanotechnology up to very large scales that span whole regions, e.g. water management systems, electric power distribution systems, or even global systems (e.g. the global positioning system, GPS). The level of advancement in the fields also varies wildly, from emerging techniques (again, nanotechnology) to trusted techniques that have been applied for centuries (architecture, hydraulic works). Nonetheless, the disciplines share one important aspect: engineering aims at designing and manufacturing systems that interface with the world around them.
Systems designed by engineers are often meant to influence their environment: to manipulate it, to move it, to stabilize it, to please it, and so on. To enable such actuation, these systems need information, e.g. values of physical quantities describing their environments and possibly also describing themselves. Two types of information sources are available: prior knowledge and empirical knowledge. The latter is knowledge obtained by sensorial observation. Prior knowledge is the knowledge that was already there before a given observation became available (this does not imply that prior knowledge is obtained without any observation). The combination of prior knowledge and empirical knowledge leads to posterior knowledge.
Content
- Introduction
- Detection and Classification
- Parameter Estimation
- State Estimation
- Supervised Learning
- Feature Extraction and Selection
- Unsupervised Learning
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