Differing from the long-term prediction used in the modern speech codec, the standard of the internet low bit rate codec (iLBC) independently encodes the residual of the linear predictive coding (LPC) frame by frame. In this paper, a complexity scalability design is proposed for the coding of the dynamic codebook search in the iLBC speech codec. In addition, a trade-off between the computational complexity and the speech quality can be achieved by dynamically setting the parameter of the proposed approach. Simulation results show that the computational complexity can be effectively reduced with imperceptible degradation of the speech quality.

A secret image transmission scheme based on vector quantization (VQ) and a secret codebook is proposed in this article. The goal of this scheme is to transmit a set of good-quality images secretly via another high-quality cover image with the same image size. In order to reduce the data size of secret images, the images are encoded by an adaptive codebook. To guarantee the visual quality of secret images, the adaptive codebook applied at the transmitter is transmitted to the receiver secretly as well. Moreover, to enhance the security of the proposed scheme and to compact the data size of the codebook, the adaptive codebook is encoded based on VQ using another codebook generated from the cover image. Experiments show impressive results.

In this paper an algebraic trellis vector quantization (ATVQ) that introduces algebraic codebooks into trellis coded vector quantization (TCVQ) structure is presented. Low encoding complexity and minimum memory storage requirements are achieved using the proposed approach. It exploits advantages of both the TCVQ and the algebraic codebooks to know the delayed decision, the codebook widening, the low computational complexity and the no storage of codebook. This novel vector quantization scheme is used to encode the wideband speech line spectral frequencies (LSF) parameters. Experimental results on wideband speech have shown that ATVQ yields the same performance as the traditional split vector quantization (SVQ) and the TCVQ in terms of spectral distortion (SD). It can achieve a transparent quality at 47 bits/frame with a considerable reduction of memory storage and computation complexity when compared to SVQ and TCVQ.

The distributed antenna system (DAS) offers significant power savings but only if the antennas are properly located. In this letter, we convert antenna location optimization to the codebook design problem. For the widely studied circular-layout DAS with uniform user distribution, we derive closed-form expressions for antenna locations that yield near-optimal performance. For more general user distribution and antenna topology, the codebook design algorithms can provide numerical optimization results with acceptable performance and low complexity.

In this paper, we propose a multi-stage hybrid scheduling scheme for codebook-based precoding systems, which provides a framework to apply different scheduling criterions at different scheduling stages for selecting user equipment (UEs). Numerical simulation results show that the proposed scheme effectively fills the performance gap between maximum carrier-to-interference (Max C/I) power ratio and Proportional Fairness (PF) methods, and provides an important means at the media access control (MAC) layer to lever between aggregate cellular throughput and geometry-specific per-user fairness, in order to meet the requirements of more precise quality of service (QoS) provision for future mobile communication systems.

Codebook based multiple-input multiple-output (MIMO) precoding can significantly improve the system spectral efficiency with limited feedback and has been accepted as one of the most promising techniques for the Evolved UTRA (E-UTRA). Compared with single-user (SU) MIMO, multi-user (MU) MIMO can further improve the system spectral efficiency due to increased multi-user diversity gain. MU-MIMO is preferred for the case of a large number of users,when the total feedback overhead will become a problem. In order to reduce the feedback overhead, feedback of single channel quality indicator (CQI), e.g. rank 1 CQI, is required in E-UTRA currently. The main challenge is how to obtain CQIs of other ranks at Node B for rank adaptation with single CQI feedback. In this paper, an adaptive CQI update scheme at Node B based on statistical characteristics of CQI of various ranks is proposed. To further increase the accuracy of CQI at Node B for data transmission, an adaptive CQI feedback scheme is then proposed in which single CQI with the rank same as previously scheduled is fed back. Simulation results show that our proposed CQI update scheme can achieve 2.5-5% gain compared with the conventional method with fixed backoff. Moreover, with the proposed adaptive feedback scheme, 20-40% performance gain can be obtained and the performance can approach the upper bound.

In this paper, the simplified search designs for the stochastic codebook of algebraic code excited linear prediction (ACELP) for ITU-T G.729D speech coder are proposed. By using two search rounds and limiting the search range, the computational complexity of the proposed approach is only 6.25% of the full search method recommended by G.729D. In addition, the computational complexity of proposed approach is only 59% of the global pulse replacement search method recommended by G.729.1. Simulation results show that the coded speech quality evaluated by using the standard subjective and objective quality measurements is with perceptually negligible degradation.

In a codebook based precoding MIMO system, the precoding codebook significantly determines the system performance. Consequently, it is crucial to design the precoding codebook, which is related to the channel fading, antenna number, spatial correlation etc. So specific channel conditions correspond to respective optimum codebooks. In this paper, in order to obtain the optimum codebooks, a universal unitary space vector quantization (USVQ) codebook design criterion is provided, which can design the optimum codebooks for various fading and spatial correlated channels with arbitrary antenna configurations. Furthermore, the unitary space K-mean (USK) algorithm is also proposed to generate the USVQ codebook, which is iterative and convergent. Simulations show that the capacities of the precoding MIMO schemes using the USVQ codebooks are very close to those of the ideal precoding cases and outperform those of the schemes using the traditional Grassmannian codebooks and the 3GPP LTE DFT (discrete Fourier transform) codebooks.

In this letter, a codebook based multiuser MIMO precoding scheme is proposed for a space-division multiple access (SDMA) system with limited feedback. Focusing on the case of SDMA systems with two transmit antennas, a precoder codebook design is proposed based on the idea that a precoder inducing larger fluctuations in the signal to interference and noise ratio (SINR) at each link can lead to a larger gain in terms of multiuser diversity. It is shown that the proposed multiuser MIMO precoding outperforms existing multiuser MIMO techniques in terms of the average system throughput.

This paper proposes several cepstral statistics compensation and normalization algorithms which alleviate the effect of additive noise on cepstral features for speech recognition. The algorithms are simple yet efficient noise reduction techniques that use online-constructed pseudo-stereo codebooks to evaluate the statistics in both clean and noisy environments. The process yields transformations for both clean speech cepstra and noise-corrupted speech cepstra, or for noise-corrupted speech cepstra only, so that the statistics of the transformed speech cepstra are similar for both environments. Experimental results show that these codebook-based algorithms can provide significant performance gains compared to results obtained by using conventional utterance-based normalization approaches. The proposed codebook-based cesptral mean and variance normalization (C-CMVN), linear least squares (LLS) and quadratic least squares (QLS) outperform utterance-based CMVN (U-CMVN) by 26.03%, 22.72% and 27.48%, respectively, in relative word error rate reduction for experiments conducted on Test Set A of the Aurora-2 digit database.

We consider a watermark application to assist in the integrity maintenance and verification of the associated images. There is a great benefit in using WM in the context of authentication since it does not require any additional storage space for supplementary metadata, in contrast with cryptographic signatures, for instance. However there is a fundamental problem in the case of exact authentication: How to embed a signature into a cover message in such a way that it would be possible to restore the watermarked cover image into its original state without any error? There are different approaches to solve this problem. We use the watermarking method consisting of modulo addition of a mark and investigate it in detail. Our contribution lies in investigating different modified techniques of both watermark embedding and detection in order to provide the best reliability of watermark authentication. The simulation results for different types of embedders and detectors in combination with the pictures of watermarked images are given.

Machine learning and data mining algorithms are increasingly being used in the intrusion detection systems (IDS), but their performances are laggard to some extent especially applied in network based intrusion detection: the larger load of network traffic monitoring requires more efficient algorithm in practice. In this paper, we propose and design an anomaly intrusion detection (AID) system based on the vector quantization (VQ) which is widely used for data compression and high-dimension multimedia data index. The design procedure optimizes the performance of intrusion detection by jointly accounting for accurate usage profile modeling by the VQ codebook and fast similarity measures between feature vectors to reduce the computational cost. The former is just the key of getting high detection rate and the later is the footstone of guaranteeing efficiency and real-time style of intrusion detection. Experiment comparisons to other related researches show that the performance of intrusion detection is improved greatly.

A speaker identification system based on wavelet transform (WT) derived from codebook design using fuzzy c-mean algorithm (FCM) is proposed. We have combined FCM and the vector quantization (VQ) algorithm to avoid typical local minima for speaker data compression. Identification accuracies of 94% were achieved for 100 Mandarin speakers.

The AMR wideband speech codec was recently developed for high-quality wideband speech communications. Although it has an excellent performance due to expanded bandwidth of speech signal, it requires a huge amount of computation especially in codebook search. To solve this problem, this paper proposes an efficient codebook search method for AMR wideband codec. Starting from a poorly performing initial codevector, the proposed method enhances the performance of the codevector iteratively by exchanging the worst pulse in the codevector with a better one after evaluating the role of each pulse. Simulations show that the AMR wideband codec adopting the proposed codebook search method provides better performance with much less computational load than that using the standard method.

This paper presents some effective methods for improving the performance of a speaker identification system. Based on the multiresolution property of the wavelet transform, the input speech signal is decomposed into various frequency subbands in order not to spread noise distortions over the entire feature space. For capturing the characteristics of the vocal tract, the linear predictive cepstral coefficients (LPCC) of the lower frequency subband for each decomposition process are calculated. In addition, a hard threshold technique for the lower frequency subband in each decomposition process is also applied to eliminate the effect of noise interference. Furthermore, cepstral domain feature vector normalization is applied to all computed features in order to provide similar parameter statistics in all acoustic environments. In order to effectively utilize all these multiband speech features, we propose a modified vector quantization as the identifier. This model uses the multilayer concept to eliminate the interference among the multiband speech features and then uses the principal component analysis (PCA) method to evaluate the codebooks for capturing a more detailed distribution of the speaker's phoneme characteristics. The proposed method is evaluated using the KING speech database for text-independent speaker identification. Experimental results show that the recognition performance of the proposed method is better than those of the vector quantization (VQ) and the Gaussian mixture model (GMM) using full-band LPCC and mel-frequency cepstral coefficients (MFCC) features in both clean and noisy environments. Also, a satisfactory performance can be achieved in low SNR environments.

This letter presents the advantages of a cascaded algebraic codebook structure at relatively high bit-rates. The cascaded structure that consists of two stages provides flexible pulse combinations due to an additional gain term in the second stage. The perceptual quality of the cascaded structure can be further improved by using a gain re-estimation scheme. Experiments confirm that the cascaded structure has a big advantage in terms of quality and complexity as the bit-rate becomes higher.

This paper proposes a new multistage technique of algebraic codebook in CELP coders called Trellis Search inspired from the Trellis Coded Quantization (TCQ). This search technique is implemented into the fixed codebook of the standard G.729 for objective evaluation on a large corpus of a testing speech database. Simulations results show that in terms of computer execution time the proposed search scheme reduces the codebook search by approximately 23% compared to the time of focused search used in the standard G.729. This yields to a reduction of about 8% in the computer execution time of the coder at the cost of a slight degradation of speech quality but perceptually not noticeable. Moreover, this new technique shows better speech quality than the G.729A at the expense of a higher complexity.

Finite-state vector quantization (FSVQ) is a well-known block encoding technique for digital image compression at low bit rate application. In this paper, an improved feature map finite-state vector quantization (IFMFSVQ) algorithm using three-sided side-match prediction is proposed for image coding. The new three-sided side-match improves the prediction quality of input blocks. Precoded blocks are used to alleviate the error propagation of side-match. An edge threshold is used to classify the blocks into nonedge or edge blocks to improve bit rate performance. Furthermore, an adaptive method is also obtained. Experimental results reveal that the new IFMFSVQ reduces bit rate significantly maintaining the same subjective quality, as compared to the basic FMFSVQ method.

This letter presents text-independent speaker identification results for telephone speech. A speaker identification system based on Karhunen-Loeve transform (KLT) derived from codebook design using genetic algorithm (GA) is proposed. We have combined genetic algorithm (GA) and the vector quantization (VQ) algorithm to avoid typical local minima for speaker data compression. Identification accuracies of 91% were achieved for 100 Mandarin speakers.

A quasi-periodic signal is a periodic signal with period and amplitude variations. Several physiological signals, including the electrocardiogram (ECG), can be treated as quasi-periodic. Vector quantization (VQ) is a valuable and universal tool for signal compression. However, compressing quasi-periodic signals using VQ presents several problems. First, a pre-trained codebook has little adaptation to signal variations, resulting in no quality control of reconstructed signals. Secondly, the periodicity of the signal causes data redundancy in the codebook, where many codevectors are highly correlated. These two problems are solved by the proposed codebook replenishment VQ (CRVQ) scheme based on a bar-shaped (BS) codebook structure. In the CRVQ, codevectors can be updated online according to signal variations, and the quality of reconstructed signals can be specified. With the BS codebook structure, the codebook redundancy is reduced significantly and great codebook storage space is saved; moreover variable-dimension (VD) codevectors can be used to minimize the coding bit rate subject to a distortion constraint. The theoretic rationale and implementation scheme of the VD-CRVQ is given. The ECG data from the MIT/BIH arrhythmic database are tested, and the result is substantially better than that of using other VQ compression methods.