Codebook

About: Codebook is a research topic. Over the lifetime, 8492 publications have been published within this topic receiving 115995 citations.

Supervised dictionary learning for music genre classification

Abstract: This paper concerns the development of a music codebook for summarizing local feature descriptors computed over time. Comparing to a holistic representation, this text-like representation better captures the rich and time-varying information of music. We systematically compare a number of existing codebook generation techniques and also propose a new one that incorporates labeled data in the dictionary learning process. Several aspects of the encoding system such as local feature extraction and codeword encoding are also analyzed. Our result demonstrates the superiority of sparsity-enforced dictionary learning over conventional VQ-based or exemplar-based methods. With the new supervised dictionary learning algorithm and the optimal settings inferred from the performance study, we achieve state-of-the-art accuracy of music genre classification using just the log-power spectrogram as the local feature descriptor. The classification accuracies for benchmark datasets GTZAN and IS-MIR2004Genre are 84.7% and 90.8%, respectively.

Trellis Coded Line Packing: Large Dimensional Beamforming Vector Quantization and Feedback Transmission

Abstract: In this paper we study the beamforming vector quantization and feedback transmission problem for a cooperative transmission environment. Feedback is the primary means of providing the transmitter with channel state information (CSI) in a frequency division duplex (FDD) system. The conventional codebook approach uses a common codebook at the transmitter and at the receiver, while the feedback takes the form of the index of the codebook. This approach has a complexity that scales exponentially with the number of transmit antennas M, making the approach less favorable when M is large. We propose to use trellis-based quantization to reduce the complexity to grow linearly in M. A codebook design criteria is derived for the trellis-based quantizer. We also present three enhancements to the base scheme, each giving 0.2-0.8 dB gain. These enhancements address issues relevant to feedback error, trellis termination, and unequal path-loss from different transmission points. Performance results are shown in numerical simulations.

Joint Design of Surveillance Radar and MIMO Communication in Cluttered Environments

Abstract: In this study, we consider a spectrum sharing architecture, wherein a multiple-input multiple-output communication system cooperatively coexists with a surveillance radar. The degrees of freedom for system design are the transmit powers of both systems, the receive linear filters used for pulse compression and interference mitigation at the radar, and the space-time communication codebook. The design criterion is the maximization of the mutual information between the input and output symbols of the communication system, subject to constraints aimed at safeguarding the radar performance. Unlike previous studies, we do not require any time-synchronization between the two systems, and we guarantee the radar performance on all of the range-azimuth cells of the patrolled region under signal-dependent (endogenous) and signal-independent (exogenous) interference. This leads to a non-convex problem, and an approximate solution is thus introduced using a block coordinate ascent method. A thorough analysis is provided to show the merits of the proposed approach and emphasize the inherent tradeoff among the achievable mutual information, the density of scatterers in the environment, and the number of protected radar cells.

Hierarchical method for foreground detection using codebook model

Abstract: This study presents a new hierarchical scheme with coarse level and fine level for foreground detection using codebook model. The code book is mainly used to compress information to achieve high efficient processing speed. In the coarse level, six intensity values are employed to represent a block. The algorithm extends the concept of the Block Truncation Coding (BTC), and thus it can further improve processing efficiency. In detail, the coarse level is divided into two stages: Level one can increase processing speed and reduce noises without increasing False Positive (FP) rate; level two can increase detected precision of level one. Fine level can further enhance precision in coarse level. Moreover, this study also presents a new color model which can classify an input pixel as shadow, highlight, background, or foreground with the match function. This model can also cooperate with the Mixture of Gaussian (MOG) to remove shadow and thus enhances MOG's performance. As documented in the experimental results, the proposed algorithm can provide superior performance to that of the former Codebook (CB) approach.

A two codebook format for robust quantization of line spectral frequencies

Abstract: An important problem in speech coding is the quantization of linear predictive coefficients (LPCs) with the smallest possible number of bits while maintaining robustness to a large variety of speech material and transmission media. Since direct quantization of LPCs is known to be unsatisfactory, the authors consider this problem for an equivalent representation, namely, the line spectral frequencies (LSFs). To achieve an acceptable level of distortion a scalar quantizer for LSFs requires a 36 bit codebook. The authors derive a 30 bit two-quantizer scheme which achieves a performance equivalent to this scalar quantizer. The two-quantizer format consists of both a vector and a scalar quantizer such that for each input, the better quantizer is used. The vector quantizer is designed from a training set that reflects the joint density (for coding efficiency) and which ensures coverage (for robustness). The scalar quantizer plays a pivotal role in dealing better with regions of the space that are sparsely covered by its vector quantizer counterpart. A further reduction of 1 bit is obtained by formulating a new adaptation algorithm for the vector quantizer and doing a dynamic programming search for both quantizers. The method of adaptation takes advantage of the ordering of the LSFs and imposes no overhead in memory requirements. The dynamic programming search is feasible due to the ordering property. Subjective tests in a speech coder reveal that the 29 bit scheme produces equivalent perceptual quality to that when the parameters are unquantized. >