Digital Signal Processing: DSP and Applications, Edition: by Dag Stranneby

By Dag Stranneby

This e-book is a uniquely sensible DSP textual content which locations the emphasis on knowing the rules and functions of DSP with not less than arithmetic. in a single quantity, it covers a extensive region of electronic sign processing platforms akin to A/D and D/A converters, adaptive filters, spectral estimation, neural networks, Kalman filters, fuzzy common sense, info compression, mistakes correction and DSP programming. Many classes will locate that this e-book will substitute numerous texts at the moment in use.

the extent is perfect for introductory collage modules, and related classes reminiscent of HNC/D. As DSP has grow to be studied at a reduce educational point over contemporary years this article meets a real want. it's also appropriate to be used on business education classes and excellent as a reference textual content for execs.

A readable advent to the sensible program of DSP
Broad assurance of the topic capacity this may conceal a standard undergraduate module in exactly one book
Practical concentration with maths taken care of as a pragmatic device - no longer a sophisticated maths textual content

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Extra resources for Digital Signal Processing: DSP and Applications, Edition: 1st

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0 1 Watermarked Image ... ... Additive Embedding 150 50 148 ... 4 The watermark embedding procedure of additive watermarking in the spatial domain. Two critical issues to consider in the additive watermarking are imperceptibility and the need of the original image to identify the embedded message. In order to enhance imperceptibility, a big value is not embedded to a single pixel, but to a block of pixels [7, 8]. 5 shows an example of the block-based additive watermarking. First, a 3 × 3 block is selected for embedding a watermark by adding 99.

When the signal becomes nonperiodic, its period becomes infinite and its spectrum becomes continuous. An image is considered as a spatially varying function. Fourier transform decomposes such an image function into a set of orthogonal functions, and can transform the spatial intensity image into its frequency domain. From continuous form, one can obtain the form for discrete time images. 1 (a) An 8-bit pixel with a value of 130. (b) The value is changed to 131 after the LSB substitution. (c) The value is changed to 2 after the MSB substitution.

2002. [8] Wong, P. W. ” In Proc. IEEE Int. Conf. Image Processing. Chicago, 1998. [9] Celik, M. , et al. ” IEEE Trans. Image Processing 11 (2002): 585. , and E. Delp. ” In Proc. Int. Conf. Imaging Science, Systems and Technology. Las Vegas, NV, 1997. , and T. Kaskalis. ” In Proc. IEEE Workshop on Nonlinear Signal and Image Processing, Neos Marmaras, Greece, 1995, 460. [12] Caronni, G. ” In Proc. Reliable IT Systems. Germany: Viewveg, 1995. , and L. O’Gorman. ” IEEE Computer Mag. 29 (1996): 101.

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