General theory of information transfer: Updated

We report on ideas, problems and results, which occupied us during the past decade and which seem to extend the frontiers of information theory in several directions. The main contributions concern information transfer by channels. There are also new questions and some answers in new models of source coding. While many of our investigations are in an explorative state, there are also hard cores of mathematical theories. In particular we present a unified theory of information transfer, which naturally incorporates Shannon's theory of information transmission and the theory of identification in the presence of noise as extremal cases. It provides several novel coding theorems. On the source coding side we introduce data compression for identification. Finally we are led beyond information theory to new concepts of solutions for probabilistic algorithms.

The original paper [R. Ahlswede, General theory of information transfer, Preprint 97-118, SFB 343 Diskrete Strukturen in der Mathematik, Universität Bielefeld, 1997] gave to and received from the ZIF-project essential stimulations which resulted in contributions added as GTIT-Supplements “Search and channels with feedback” and “Noiseless coding for multiple purposes: a combinatorial model”.

Other contributions—also to areas initiated—are published in the recent book [R. Ahlswede et al. (Eds.), General Theory of Information Transfer and Combinatorics, Lecture Notes in Computer Science, vol. 4123, Springer, Berlin, 2006].

The readers are advised to study always the pioneering papers in a field—in this case the papers [R. Ahlswede, G. Dueck, Identification via channels, IEEE Trans. Inform. Theory 35 (1989) 15–29; R. Ahlswede, G. Dueck, Identification in the presence of feedback—a discovery of new capacity formulas, IEEE Trans. Inform. Theory 35 (1989) 30–39] on identification. It is not only the most rewarding way to come to new ideas, but it also helps to more quickly grasp the more advanced formalisms without going through too many technicalities. Perhaps also the recent Shannon Lecture [R. Ahlswede, Towards a General Theory of Information Transfer, Shannon Lecture at ISIT in Seattle 13th July 2006, IEEE Information Theory Society Newsletter, 2007], aiming at an even wider scope, gives further impetus.     

LPV identification of a turbocharged diesel engine

This work proposes a methodology of identifying linear parameter varying (LPV) models for nonlinear systems. First, linear local models in some operating points, by applying standard identifications procedures for linear systems in time domain, are obtained. Next, a LPV model with linear fractional dependence (LFR) with respect to measured variables is fitted with the condition of containing all the linear models identified in previous step (differential inclusion). The fit is carried out using nonlinear least squares algorithms. Finally, this identification methodology will then be applied to a nonlinear turbocharged diesel engine.     

Linear Dynamical Identification: An Integral Transform seen as a Complex Wavelet Transform

This paper presents a technique that allows the direct linearidentification of frequency response functions from the computation ofa weighted integral transform. This transform allows toemphasize the influence of the poles and zeros of the frequencyresponse functions its formation is based on the Cauchy--Weierstrass theorem. It isthen shown that this transform is directly linked to a complex wavelettransform. This representation with a wavelet transform provides abetter understanding of the amplification effects of the weightedintegral transform and allows the singularities analysis.     

A model of hysteresis with two inputs

We formulate and analyze a new model of vector hysteresis for the case of two-input signals. We prove the essential mathematical properties of this model and we present the solutions to two identification problems connected with our model.     

Identification of Transverse Crack Position and Depth in Rotor Systems

This paper introduces a method for the identification of the position and the depth of a transverse crack in a rotor system, by using vibration measurements. As it is reported in literature and from field experience, a transverse crack modifies the dynamic behaviour of the rotor, generating in a horizontal axis shaft periodical vibrations with 1x, 2x and 3x rev. components. A model-based diagnostic approach and a least-squares identification method in the frequency domain are used for the crack localisation along the rotor. The crack depth is calculated by comparing the static bending moment, due to the rotor weight and to the bearing alignment conditions, to the identified 'equivalent' periodical bending moment, which simulates the crack. Finally, the validation of the proposed method is carried out statically and dynamically by means of experimental results obtained on a test-rig.     

结构模态参数的时序分析(ARMAV模型)识别法

本文简述了用时间序列分析(ARMAV 模型)识别结构模态参数的原理,对建模方法进行了分析,并对建模分析中至关重要的初值选择问题进行了讨论,提出了一种有效的初值的选取方法;在模拟计算部分中,用 Wilson-θ积分法模拟了一个三个自由度的振动和低信噪比、大阻尼振动和密集模态等复杂情形,对用时序方法(ARMAV 模型)识别模态参数的能力进行了检验;最后通过对实验数据进行有效的预处理后,用时序方法(ARMAV 模型)识别出一个真实结构(圆盘)的第一、二阶模态参数,并得到结构的完整振型.     

基于时间响应函数的结构阻尼识别方法比较

研究了3种基于时间响应函数的结构阻尼识别方法, 包括对数衰减法、希尔 伯特方法和小波方法. 给出了3种方法的实现算法, 分析了对密集模态的识别能力. 构造仿真算例, 采用3种方法识别了5{\%}, 10{\%}和30{\%}噪声条件下的模态阻尼. 结果表明, 小波方法比对数衰减法和希尔伯特方法具有更好的噪声鲁棒性. 采用小波方法分析了润扬大桥结构健康监测系统获得的实测数据, 识别出了润扬大桥悬索桥前6阶模态参数, 第2阶和第3阶模态频率相差仅为0.015\,Hz. 研究表明, 小波方法具备噪声条件下密集模态的识别能力, 是工程中阻尼识别的优选方法.     

A systematic approach to reliably characterize soils based on Bevameter testing

Although a lot of information about soil parameter identification exists in literature, there is currently no algorithm who makes use both of state of the art identification methodologies and incorporating statistical analysis. In this paper a state of the art soil parameter identification method is presented including the calculation of its standard deviations and a proper weighting of the objective function. With this algorithm and a Bevameter with advanced sensor and actuator technology a test campaign is started to find a reliable soil preparation, which is applicable to a large planetary rover performance testbed. Furthermore, the preparation method has to be valid and stable for various types of dry, granular and frictional soils, typically used for planetary rover testing in space robotics, since the result of pre-tests show that the soil parameters are highly depending on the preparation. Besides preparation, the soil parameters are also influenced by different Bevameter test setup variables. Thus, the effect of the penetration velocity as well as the penetration tool geometry for pressure–sinkage tests on soil parameters is investigated. For shear tests the influence of the dimension of the shear ring is analysed as well as the variation of the grouser height, the number of the grousers and the increase of the rotational shear velocity. The results of the extensive test campaign are evaluated by the proposed identification algorithms.     

Identification of time-varying hysteretic structures using wavelet multiresolution analysis

In this paper, a wavelet multiresolution technique is proposed to identify time-varying properties of hysteretic structures. It is well known that arbitrary transient functions can be effectively and accurately approximated using wavelet multiresolution expansions due to wavelet's good time-frequency localization property. By decomposing the time-varying parameters with wavelet multiresolution expansion, a time-varying parametric identification problem can be transformed into a time-invariant non-parametric one. The identification in the time-invariant wavelet multiresolution domain can be achieved by choosing a wavelet basis function and performing a suitable parameter estimation technique. Since wavelet representation of arbitrary signal uses only a small number of terms, the orthogonal forward regression algorithm can be adopted for significant term selection and parameter estimation. Single and multiple degrees of freedom Bouc-Wen hysteretic structures with gradual and abrupt varying properties are used to illustrate the proposed approach. Results show that the wavelet multiresolution technique can identify and track the time-varying hysteretic parameters quite accurately. The effect of measurement noise is also studied. It is found that the presence of noise would affect more on the damping ratios and the Bouc-Wen parameters but less on the equivalent stiffness coefficients.     

Bias in modal parameters using the direct and iterative RFP identification procedures

In the rational fraction polynomial method [1] the identification of modal parameters is obtained through a direct linear least-square optimization technique but a particular form of fitting error is minimized. An iterative algorithm has been recently developed which uses the true fitting error [2]. In this paper a statistical analysis is developed to estimate the bias effects on the identified parameters when the data are polluted with noise. Both the direct and iterative procedures are considered. Numerical simulations are used to validate the results predicted by the theoretical analysis, which shows that the iterative approach is by far more efficient than the direct method.A first version of this paper was presented at 17th Int. Seminar on Modal Analysis, Leuven (Belgium), 23–25 September 1992, and preprinted in the Proceedings.