This book provides an intermediate-level exposition of the exciting world of neuro-computers. It includes several case studies that use real-world sensor data sets as a benchmark to demonstrate how the new learning paradigm can be used by a neuro-computer designer to develop solutions with better fault-tolerance and generalization properties. It also introduces new genetic operators that consistently outperform the conventional cross-over and mutation--based genetic algorithms. INV STAT: Normal

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