基于人类视觉特性的纹理分割方法

纹理分割是将一幅图像依据纹理不同分成若干个不同的区域,目前广泛采用的是利用滤波器族(如Gabor)对图像进行分解。但由于图像纹理表现的各异性,通常在滤波器参数的选择上不能做到自适应,导致提取的特征不明显,分类效果不好,使用范围受限。文中提出了一种基于人类视觉系统(Human Visual System,HVS)机理的纹理分割方法,不但可以模拟人类观察纹理直觉处理阶段确定纹理区的个数并且粗略地划分区域,而且可以模拟专注处理阶段自动选择Gabor滤波器的个数及参数。该算法符合HVS区分纹理机理,计算过程简单、方便。针对各纹理选取的特征明显,分类效果好。     

Linear periodically time-varying discrete-time systems: Aliasing and LTI approximations

Linear periodically time-varying (LPTV) systems are abundant in control and signal processing; examples include multirate sampled-data control systems and multirate filter-bank systems. In this paper, several ways are proposed to quantify aliasing effect in discrete-time LPTV systems; these are associated with optimal time-invariant approximations of LPTV systems using operator norms.     

基于过采样DFT滤波器组的GNSS窄带干扰抑制方法

对于全球导航卫星系统(GNSS)接收机而言,窄带干扰十分常见并且危害较大。对此提出一种基于过采样离散傅里叶变换(DFT)滤波器组的频域窄带干扰抑制技术。与传统的基于加窗DFT处理的方法相比,这种方法能够更好地减小干扰信号频谱泄露问题;而与基于临界采样DFT滤波器组方法相比,这种方法能够更加有效地降低导航信号的畸变问题,特别适合在卫星导航接收机中应用。理论分析和仿真结果表明,基于过采样DFT滤波器组的新方法具有更强的窄带干扰抑制能力和更小的插入损耗。     

Using redundant parallel architecture to improve speaker recognition performance

In this paper, we propose two kinds of modifications in speaker recognition. First, the correlations between frequency channels are of prime importance for speaker recognition. Some of these correlations are lost when the frequency domain is divided into sub-bands. Consequently we propose a particularly redundant parallel architecture for which most of the correlations are kept. Second, generally a log transformation used to modify the power spectrum is done after the filter-bank in the classical spectrum calculation. We will see that performing this transformation before the filter bank is more interesting in our case. In the processing of recognition, the Gaussian mixture model (GMM) recognition arithmetic is adopted. Experiments on speech corrupted by noise show a better adaptability of this approach in noisy environments, compared with a conventional device, especially when pruning of some recognizers is performed.     

Interactive multi-scale exploration for volume classification

Filter banks are a class of signal processing techniques that can be used to reveal the local energy of a signal at multiple scales. Utilizing such filtering allows us to consider local texture and other data characteristics, and permits volume classification and visualization that cannot be accomplished easily using conventional, transfer function-based methods. Our filter bank approach increases the dimensionality, and thus, the complexity of the classification task. We have therefore developed an interactive user interface for specifying and visualizing these higher dimensional classifiers, which enables volume data exploration and visualization in a filter-bank space. We demonstrate that this technique is particularly effective for the classification of noisy data, and for classifying regions that are difficult to approach using conventional methods.     

Using redundant parallel architecture to improve speaker recognition performance

In this paper, we propose two kinds of modifications in speaker recognition. First, the correlations between frequency channels are of prime importance for speaker recognition. Some of these correlations are lost when the frequency domain is divided into sub-bands. Consequently we propose a particularly redundant parallel architecture for which most of the correlations are kept. Second, generally a log transformation used to modify the power spectrum is done after the filter-bank in the classical spectrum calculation. We will see that performing this transformation before the filter bank is more interesting in our case. In the processing of recognition, the Gaussian mixture model （GMM） recognition arithmetic is adopted. Experiments on speech corrupted by noise show a better adaptability of this approach in noisy environments, comoared with a conventional device, esoeciallv when oruning of some recognizers is performed.     

Pitch estimation of speech and music sound based on multi-scale product with auditory feature extraction

The pitch is a crucial parameter in speech and music signals. However, due to severe noisy conditions, missing harmonics, unsuitable physical vibration, the determination of pitch presents a great challenge when desiring to get a good accuracy. In this paper, we propose a method for pitch estimation of speech and music sounds. Our method is based on the fast Fourier transform (FFT) of the multi-scale product (MP) provided by a feature auditory model of the sound signals. The auditory model simulates the spectral behaviour of the cochlea by a gammachirp filter-bank, and the out/middle ear filtering by a low-pass filter. For the two output channels, the FFT function of the MP is computed over frames. The MP is based on constituting the product of the speech and music wavelet transform coefficients at three scales. The experimental results show that our method estimates the pitch with high accuracy. Besides, our proposed method outperforms several other pitch detection algorithms in clean and noisy environments.     

Parallel strategies for 2D Discrete Wavelet Transform in shared memory systems and GPUs

In this work, we analyze the behavior of several parallel algorithms developed to compute the two-dimensional discrete wavelet transform using both OpenMP over a multicore platform and CUDA over a GPU. The proposed parallel algorithms are based on both regular filter-bank convolution and lifting transform with small implementations changes focused on both the memory requirements reduction and the complexity reduction. We compare our implementations against sequential CPU algorithms and other recently proposed algorithms like the SMDWT algorithm over different CPUs and the Wippig&Klauer algorithm over a GTX280 GPU. Finally, we analyze their behavior when algorithms are adapted to each architecture. Significant execution times improvements are achieved on both multicore platforms and GPUs. Depending on the multicore platform used, we achieve speed-ups of 1.9 and 3.4 using two and four processes, respectively, when compared to the sequential CPU algorithm, or we obtain speed-ups of 7.1 and 8.9 using eight and ten processes. Regarding GPUs, the GPU convolution algorithm using the GPU shared memory obtains speed-ups up to 20 when compared to the CPU sequential algorithm.     

A Comparative Study of Several Feature Transformation and Learning Methods for Phoneme Classification

This paper examines the applicability of some learning techniques for speech recognition, more precisely, for the classification of phonemes represented by a particular segment model. The methods compared were the IB1 algorithm (TiMBL), ID3 tree learning (C4.5), oblique tree learning (OC1), artificial neural nets (ANN), and Gaussian mixture modeling (GMM), and, as a reference, a hidden Markov model (HMM) recognizer was also trained on the same corpus. Before feeding them into the learners, the segmental features were additionally transformed using either linear discriminant analysis (LDA), principal component analysis (PCA), or independent component analysis (ICA). Each learner was tested with each transformation in order to find the best combination. Furthermore, we experimented with several feature sets, such as filter-bank energies, mel-frequency cepstral coefficients (MFCC), and gravity centers. We found LDA helped all the learners, in several cases quite considerably. PCA was beneficial only for some of the algorithms, and ICA improved the results quite rarely and was bad for certain learning methods. From the learning viewpoint, ANN was the most effective and attained the same results independently of the transformation applied. GMM behaved worse, which shows the advantages of discriminative over generative learning. TiMBL produced reasonable results; C4.5 and OC1 could not compete, no matter what transformation was tried.     

基于Mel子带参数化特征的自动鸟鸣识别

针对自然复杂声学环境下基于鸟鸣的物种分类问题,提出了一种基于Mel子带参数化特征的鸟鸣自动识别方法。采用高斯混合模型（GMM）拟合连续声学监测数据分帧后的对数能量分布,选取高似然率的数据帧组成候选声音事件完成自动分段。在谱图域对相应片段采用Mel带通滤波器组滤波处理,然后基于自回归模型（AR）分别建模各个子带输出的随时间变化的能量序列,得到能够描述不同种类鸟鸣信号时频特性的参数化特征。最后利用支持向量机（SVM）分类器进行分类识别。基于野外自然环境11种鸟鸣信号开展了自动分段与识别实验,所提方法针对各类鸟鸣的查准率、查全率以及F1度量均不低于89%,明显优于现有基于纹理特征的方法,更适用于野外鸟类连续声学监测领域的自动数据分析需求。     

Controlled-coverage discrete S-transform (CC-DST): Theory and applications

The S-transform (ST) is a popular linear time-frequency (TF) transform with hybrid characteristics from the short-time Fourier transform (STFT) and the wavelet transform. It enables a multi-resolution TF analysis and returns globally referenced local phase information, but its expensive computational requirements often overshadow its other desirable features. In this paper, we develop a fully discrete ST (DST) with a controllable TF sampling scheme based on a filter-bank interpretation. The presented DST splits the analyzed signal into subband channels whose bandwidths increase progressively in a fully controllable manner, providing a frequency resolution that can be varied and made as high as required, which is a desirable property for processing oscillatory signals lacked by previously presented DSTs. Thanks to its flexible sampling scheme, the behavior of the developed transform in the TF domain can be adjusted easily; with specific parameter settings, for example, it samples the TF domain dyadically, while by choosing different settings, it may act as a STFT. The spectral partitioning is performed through asymmetric raised-cosine windows whose collective amplitude is unitary over the signal spectrum to ensure that the transform is easily and exactly invertible. The proposed DST retains all the appealing properties of the original ST, representing a local image of the Fourier transform; it requires low computational complexity and returns a modest number of TF coefficients. To confirm its effectiveness, the developed transform is utilized for different applications using real-world and synthetic signals.     

Speech Separation Methodology for Hearing Aid

In the design of hearing aids (HA), the real-time speech-enhancement is done. The digital hearing aids should provide high signal-to-noise ratio, gain improvement and should eliminate feedback. In generic hearing aids the performance towards different frequencies varies and non uniform. Existing noise cancellation and speech separation methods drops the voice magnitude under the noise environment. The performance of the HA for frequency response is non uniform. Existing noise suppression methods reduce the required signal strength also. So, the performance of uniform sub band analysis is poor when hearing aid is concern. In this paper, a speech separation method using Non-negative Matrix Factorization (NMF) algorithm is proposed for wavelet decomposition. The Proposed non-uniform filter-bank was validated by parameters like band power, Signal-to-noise ratio (SNR), Mean Square Error (MSE), Signal to Noise and Distortion Ratio (SINAD), Spurious-free dynamic range (SFDR), error and time. The speech recordings before and after separation was evaluated for quality using objective speech quality measures International Telecommunication Union -Telecommunication standard ITU-T P.862.     

Bayesian Object Localisation in Images

A Bayesian approach to intensity-based object localisation is presented that employs a learned probabilistic model of image filter-bank output, applied via Monte Carlo methods, to escape the inefficiency of exhaustive search.An adequate probabilistic account of image data requires intensities both in the foreground (i.e. over the object), and in the background, to be modelled. Some previous approaches to object localisation by Monte Carlo methods have used models which, we claim, do not fully address the issue of the statistical independence of image intensities. It is addressed here by applying to each image a bank of filters whose outputs are approximately statistically independent. Distributions of the responses of individual filters, over foreground and background, are learned from training data. These distributions are then used to define a joint distribution for the output of the filter bank, conditioned on object configuration, and this serves as an observation likelihood for use in probabilistic inference about localisation.The effectiveness of probabilistic object localisation in image clutter, using Bayesian Localisation, is illustrated. Because it is a Monte Carlo method, it produces not simply a single estimate of object configuration, but an entire sample from the posterior distribution for the configuration. This makes sequential inference of configuration possible. Two examples are illustrated here: coarse to fine scale inference, and propagation of configuration estimates over time, in image sequences.     

Semantics and verification of monitors and systems of monitors and processes

In this paper we present a sound and complete semantics for the monitor concept of C.A.R. Hoare. First a method for specification of monitors, introduced by O.-J. Dahl, is reviewed. This method is based on the relation between the historic sequence of monitor procedure calls and the historic sequence of monitor procedure exits. Based on such specifications and our new monitor semantics we present a method by which it is possible to prove that a concrete monitor is an implementation of an abstract one. In the last part of the paper an axiomatic semantics for systems of concurrent processes and monitors is introduced. The method supports verification by separation of concerns: Properties of the communication to and from each process are proven in isolation by a usual Hoare style axiomatic semantics, while abstract monitors are also specified in isolation by the method reviewed in the first part of the paper. These properties of the components of the system are then used in a new proof rule to conclude properties of the complete system. Stein Gjessing received a Ph.D. (actually a Dr. philos.) from the University of Oslo (Norway) in 1985. Presently he is an Associate Professor at the Institute of informatics, University of Oslo, Norway. Dr. Gjessings research interests are in the area of concurrent and distributed programming, operating systems, formal specification and verification and programming languages.     

SGML and XML Document Grammars and Exceptions

The Standard Generalized Markup Language (SGML) and the Extensible Markup Language (XML) allow users to define document-type definitions (DTDs), which are essentially extended context-free grammars expressed in a notation that is similar to extended Backus–Naur form. The right-hand side of a production, called a content model, is both an extended and a restricted regular expression. The semantics of content models for SGML DTDs can be modified by exceptions (XML does not allow exceptions). Inclusion exceptions allow named elements to appear anywhere within the content of a content model, and exclusion exceptions preclude named elements from appearing in the content of a content model. We give precise definitions of the semantics of exceptions, and prove that they do not increase the expressive power of SGML DTDs when we restrict DTDs according to accepted SGML practice. We prove the following results:1. Exceptions do not increase the expressive power of extended context-free grammars.2. For each DTD with exceptions, we can obtain a structurally equivalent extended context-free grammar.3. For each DTD with exceptions, we can construct a structurally equivalent DTD when we restrict the DTD to adhere to accepted SGML practice.4. Exceptions are a powerful shorthand notation—eliminating them may cause exponential growth in the size of an extended context-free grammar or of a DTD.     

The scientific method and design and test

A few years ago, during a well-attended open Design Automation Conference benchmark forum, a panellist pointed out that “...reporting experimental results is a science and an art. A survey of the literature may reveal a consistent methodology.... Also, we should address the verification of reported results.” In retrospect, the suggestion may have hinted at the vast body of techniques commonly known as experimental design. However, this forum was not ready to expand on the subject. Most search engines currently on the Web return tens of thousands of URLs in response to keyword searches using terms such as experimental design or design of experiments. Few, if any, of these search results point to an evaluation of CAD algorithms. In contrast, the experimental design methodology, pioneered by Fischer during the 1920s in agricultural research, is now firmly established in science and manufacturing. Its application to biomedical research can save lives. Biomedical journals have strict guidelines on how to report experimental results so others may replicate experiments. A URL from a medical school points to a concise illustration of a simple experimental design flow and the terminology used. Adopting the accepted norms of experimental design will give us a scientific method to conduct, verify, and report comparative performance evaluations of CAD algorithms     

Qualitative and quantitative temporal constraints and relationaldatabases: theory, architecture, and applications

Many different applications in different areas need to deal with both: databases, in order to take into account large amounts of structured data; and quantitative and qualitative temporal constraints about such data. We propose an approach that extends: temporal databases and artificial intelligence temporal reasoning techniques and integrate them in order to face such a need. Regarding temporal reasoning, we consider some results that we proved recently about efficient query answering in the Simple Temporal Problem framework and we extend them in order to deal with partitioned sets of constraints and to support relational database operations. Regarding databases, we extend the relational model in order to consider also qualitative and quantitative temporal constraints both in the data (data expressiveness) and in the queries (query expressiveness). We then propose a modular architecture integrating a relational database with a temporal reasoner. We also consider classes of applications that fit into our approach and consider patient management in a hospital as an example     

Abstraction and approximation in fuzzy temporal logics and models

Recently, by defining suitable fuzzy temporal logics, temporal properties of dynamic systems are specified during model checking process, yet a few numbers of fuzzy temporal logics along with capable corresponding models are developed and used in system design phase, moreover in case of having a suitable model, it suffers from the lack of a capable model checking approach. Having to deal with uncertainty in model checking paradigm, this paper introduces a fuzzy Kripke model (FzKripke) and then provides a verification approach using a novel logic called Fuzzy Computation Tree Logic* (FzCTL*). Not only state space explosion is handled using well-known concepts like abstraction and bisimulation, but an approximation method is also devised as a novel technique to deal with this problem. Fuzzy program graph, a generalization of program graph and FzKripke, is also introduced in this paper in consideration of higher level abstraction in model construction. Eventually modeling, and verification of a multi-valued flip-flop is studied in order to demonstrate capabilities of the proposed models.     

Microbial ecology and bioprocess control: Opportunities and challenges

This paper aims at emphasizing the importance of a systemic approach together with new investigation tools provided by molecular biology to give new insights into microbial ecology. Through the presentation of four recently obtained results about the coexistence of species in competition on a single resource, it is argued that such an approach can have major impact on ecological problems. In the first example, we revisit the existing models of biotechnology and show how they can be updated in some sense to better describe the real world by taking into account the spatial heterogeneity in a very simple but effective way (in the sense that their qualitative predictions are in accordance with the observed data). In the second example, we show how an optimally designed biosystem may give insights to the understanding of the so-called barrier effect. The third example proposes a new explanation for coexistence, that we called “long run coexistence”, in studying the transient behavior of a high dimensional system describing N species in competition on a single substrate. Finally, a last example presents the original concept of “biological control” which refers to the use of a particular species to globally stabilize an unstable biological process.     

Information and knowledge: Nature and the conceptual model

Information is defined through the introduced concepts of an information object and an information interaction, in which the change in the state of objects-originals involves a change in their images. Information is a macro form that emerges in a nonequilibrium medium and has a dual nature as an object and as a reality. Knowledge is defined as information that is reduced to the superposition of possible states of the information object in different individual domains. Information fulfills communication functions, interactions in an individual domain, and its own functions that actualize its own validity. In terms of the mechanism of interaction, information, being a structured and not atomic object, should have “interface” elements that join it with communication objects.