Neural Network Principles and Applications

Due to the recent trend of intelligent systems and their ability to adapt with varying conditions, deep learning becomes very attractive for many researchers. In general, neural network is used to implement different stages of processing systems based on learning algorithms by controlling their weights and biases. This chapter introduces the neural network concepts, with a description of major elements consisting of the network. It also describes different types of learning algorithms and activation functions with the examples. These concepts are detailed in standard applications. The chapter will be useful for undergraduate students and even for postgraduate students who have simple background on neural networks

Chaos-Based Communication Systems

The attractive properties of chaos signal that is generated from dynamic systems motivate the researchers to explore the advantage of using this signal type as a carrier in different communication systems. In this chapter, different types of digital chaos–based communication system are discussed; in particular, digital communications where reference signal and its modulated version are transmitted together. This type is called differential coherent systems. Brief surveys on the recently developed systems are presented

Flood Monitoring and Prediction System Development [cover title]

ODOT SPR Item Number 2314The first half of this report details the design of a flooding emulation system to evaluate LiDAR-, radar-, and ultrasonic-based devices for monitoring water level rise and measure water flow speed. The second half of the report describes the incorporation of NOAA data with data collected at ODOT weather station to predict the potential of flooding