There has been a great deal of material in the area of discrete-time transforms that has been published in recent years. This book does an excellent job of presenting important aspects of such material in a clear manner. The book has 11 chapters and a very useful appendix. Seven of these chapters are essentially devoted to the Fourier series/transform, discrete Fourier transform, fast Fourier transform (FFT), and applications of the FFT in the area of spectral estimation. Chapters 8 through 10 deal with many other discrete-time transforms and algorithms to compute them. Of these transforms, the KarhunenLoeve, the discrete cosine, and the Walsh-Hadamard transform are perhaps the most well-known. A lucid discussion of number theoretic transforms i5 presented in Chapter 11. This reviewer feels that the authors have done a fine job of compiling the pertinent material and presenting it in a concise and clear manner. There are a number of problems at the end of each chapter, an appreciable number of which are challenging. The authors have included a comprehensive set of references at the end of the book. In brief, this book is a valuable contribution to the general areas of signal processing and communications. It can be used for a graduate level course in perhaps two ways. One would be to cover the first seven chapters in great detail. The other would be to cover the whole book by focussing on different topics in a selective manner. This book  by  Elliott  and Rao  is extremely  useful to researchers/engineers who are working  in the areas of signal processing and communications. It i s also an excellent reference book, and hence a valuable addition to one’s library

http://ieeexplore.ieee.org/iel5/5/31347/01457444.pdf

Multirate digital signal processing

In embodiments, the present invention provides a method and system for delivery of content on a mobile media platform, providing an automated tag processing facility, and delivering content to a mobile device, wherein content delivery is based at least in part on the automated tag processing.

Automated Content Tag Processing for Mobile Media

A modular intelligent transportation system, comprising an environmentally protected enclosure, a system communications bus, a processor module, communicating with said bus, having a image data input and an audio input, the processor module analyzing the image data and/or audio input for data patterns represented therein, having at least one available option slot, a power supply, and a communication link for external communications, in which at least one available option slot can be occupied by a wireless local area network access point, having a communications path between said communications link and said wireless access point, or other modular components.

Modular intelligent transportation system

Techniques are described for encoding and decoding digital video data using macroblocks that are larger than the macroblocks prescribed by conventional video encoding and decoding standards. For example, the techniques include encoding and decoding a video stream using macroblocks comprising greater than 16×16 pixels. In one example, an apparatus includes a video encoder configured to encode a coded unit comprising a plurality of video blocks, wherein at least one of the plurality of video blocks comprises a size of more than 16×16 pixels and to generate syntax information for the coded unit that includes a maximum size value, wherein the maximum size value indicates a size of a largest one of the plurality of video blocks in the coded unit. The syntax information may also include a minimum size value. In this manner, the encoder may indicate to a decoder the proper syntax decoder to apply to the coded unit.

Video coding with large macroblocks

A method of delivering an audio and/or visual media file including, for example, one or more of full or partial master recordings of songs, musical compositions, ringtones, videos, films, television shows, personal recordings, animation and combinations thereof, over the air wirelessly, from one or more servers to an electronic device with or without an Internet connection, said method comprising transmitting and audio and/or visual media file in compressed format to said electronic device, and wherein the electronic device is effective to receive said audio and/or visual file and playback said audio and/or visual content on demand by a user.

Media delivery platform

An audio encoder implements multi-channel coding decision, band truncation, multi-channel rematrixing, and header reduction techniques to improve quality and coding efficiency. In the multi-channel coding decision technique, the audio encoder dynamically selects between joint and independent coding of a multi-channel audio signal via an open-loop decision based upon (a) energy separation between the coding channels, and (b) the disparity between excitation patterns of the separate input channels. In the band truncation technique, the audio encoder performs open-loop band truncation at a cut-off frequency based on a target perceptual quality measure. In multi-channel rematrixing technique, the audio encoder suppresses certain coefficients of a difference channel by scaling according to a scale factor, which is based on current average levels of perceptual quality, current rate control buffer fullness, coding mode, and the amount of channel separation in the source. In the header reduction technique, the audio encoder selectively modifies the quantization step size of zeroed quantization bands so as to encode in fewer frame header bits.

Quality improvement techniques in an audio encoder

An audio encoder and decoder use architectures and techniques that improve the efficiency of multi-channel audio coding and decoding. The described strategies include various techniques and tools, which can be used in combination or independently. For example, an audio encoder performs a pre-processing multi-channel transform on multi-channel audio data, varying the transform so as to control quality. The encoder groups multiple windows from different channels into one or more tiles and outputs tile configuration information, which allows the encoder to isolate transients that appear in a particular channel with small windows, but use large windows in other channels. Using a variety of techniques, the encoder performs flexible multi-channel transforms that effectively take advantage of inter-channel correlation. An audio decoder performs corresponding processing and decoding. In addition, the decoder performs a post-processing multi-channel transform for any of multiple different purposes.

Multi-channel audio encoding and decoding

An audio decoder provides a combination of decoding components including components implementing base band decoding, spectral peak decoding, frequency extension decoding and channel extension decoding techniques. The audio decoder decodes a compressed bitstream structured by a bitstream syntax scheme to permit the various decoding components to extract the appropriate parameters for their respective decoding technique.

Bitstream syntax for multi-process audio decoding

A transform coder adaptively configures window sizes for transform coding in a two-pass process to maximize coding efficiency, while achieving necessary time resolution to avoid pre-echo. In a first pass, the coder places small size windows over detected transient regions of an input signal in an open-loop window configuration process. In a second pass, the coder adjusts the window size configuration according to measurements of the achieved quality in a closed-loop window configuration process. Where quality measurement shows unacceptable quantization noise, the coder increases window size. Where pre-echo is detected, the coder reduces window size within coding bit rate constraints.

Adaptive window-size selection in transform coding

An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Wei-ge Chen

Papers

Quality improvement techniques in an audio encoder

Multi-channel audio encoding and decoding

Bitstream syntax for multi-process audio decoding

Adaptive window-size selection in transform coding

Quality and rate control strategy for digital audio