In this paper, we introduce an implementation of the attribute selection algorithm, Correlation-based Feature Selection (CFS) integrated with our k-nearest neighbour (k-NN) framework. Binary neural networks underpin our k-NN and allow us to create a unified framework for attribute selection, prediction and classification. We apply the framework to a real world application of predicting bus jour...

Abstract. The Global Precipitation Measurement (GPM) mission measures global precipitation at a temporal resolution of few hours to enable close monitoring the hydrological cycle. GPM achieves this by combining observations from spaceborne radar, constellation passive microwave (PMW) sensors, and geostationary satellites. Goddard Profiling Algorithm (GPROF) is used operationally retrieve all PM...

Selection of neural network learning rates to obtain satisfactory performance from neural network controllers is a challenging problem. To assist in the selection of learning rates, this paper investigates robotic system sensitivity to neural network (NN) learning rate. The work reported here consists of experimental and simulation results. A neural network controller module, developed for the ...

This paper presents design and implementation of three new Infrared Counter-Countermeasure (IRCCM) efficient methods using Neural Network (NN), Fuzzy System (FS), and Kalman Filter (KF). The proposed algorithms estimate tracking error or correction signal when jamming occurs. An experimental test setup is designed and implemented for performance evaluation of the proposed methods. The methods v...

This paper constructs fully parallel NN hardware architecture, FPGA has been used to reduce neuron hardware by design the activation function inside the neuron without using lookup table as in most researches, to perform an efficient NN. It consist of two main parts; the first part covers network training using MATLAB program, the second part represents the hardware implementation of the traine...

A neural network (NN) filter/target-tracking system has been developed as reported in [6]. The design accepts and inputs signal data to a noise/target classifier which uses spectral estimation techniques to distinguish noise from real targets. In that design, the NN is used to calculate the coefficients of an auto regressive linear predictive filter. The current evolution of that design invokes...