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APPENDIX A - IEEE Standard for Binary Floating Point Arithmetic

	Neural Networks and Pattern Recognition Using MATLAB


		Ch.1 Pattern Classification


		Ch.2 Matrix Theory Applications


		Ch.3 Network Object Reference


		Ch.4 Bayesian Decision Theory


		Ch.5 Principal Component Analysis


		Ch.6 Intro to Neural Networks


		Ch.8 Classical Models of NN


		Ch.9 Linear Discriminant Functions


		Ch.11 Non-Parametric Techniques


		Ch.10 Multilayer Neural Networks


		Ch.7 Neural Networks


	Volume Rendering Temelleri


		Ch.1 Introduction to Volume Rendering


		Ch.2 Volume Rendering


		Ch.3 Volumetric Data


		Ch.4 Voxels and Cells


		Ch.5 Classification of VR Algorithms


		Ch.6 Optimization in Volume Rendering


		Ch.7 References


	Accelerating Volume Rendering by DSP Hardware Implementation


		Ch.1 Volume Rendering


		Ch.2 Optimization in VR


		Ch.3 Framework


		Ch.4 Choosing the Appropriate DSP Processor


		Ch.5 Implementation


	A Review of Floating Point Basics and Comparison of Dedicated Processors


		Ch.1 Binary Systems


		Ch.2 Digital Signal Processors


		Ch.3 Introduction to DSP


		Ch.4 Memory Architectures


		Ch.5 Review of DSP Processors


		Ch.6 Appropriate DSP Processor


		Ap.A - IEEE Floating Point Arithmetic


		Ap.B - IEEE Radix-Independent Floating Point


		Ap.C - Calculation of Emax and Bias

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