A method is presented for reconstructing the surface profile of a two dimensional rough surface boundary from the scattered far field data. The proposed inversion algorithm is based on the Kirchhoff approximation and in order to determine the surface profile, the numerical results illustrating the method are presented.

In the present communication we propose the application of unsupervised Artificial Neural Networks (ANN) to solve general ill-posed problems and particularly we apply them to the the estimation of the direction of arrival (DOA) of VLF/ELF radio waves. We use the wave distribution method which consists in the reconstruction of the energy distribution of magnetospheric VLF/ELF waves at the ionospheric base from observations of the wave's electromagnetic field on the ground. The present application is similar to a number of computerized tomography and image enhancement problems and the proposed algorithm can be straightforwardly extended to other applications in which observations are linearly related to unknowns. Then, we have proven the applicability and also we indicate the superiority of the ANN to the conventional methods to handle this kind of problems.

The objective of this paper is to find a parametric representation for the vocal-tract log-area function that is directly and simply related to basic acoustic characteristics of the human vocal-tract. The importance of this representation is associated with the solution of the articulatory-to-acoustic inverse problem, where a simple mapping from the articulatory space onto the acoustic space can be very useful. The method is as follows: Firstly, given a corpus of log-area functions, a parametric model is derived following a factor analysis technique. After that, the articulatory space, defined by the parametric model, is filled with approximately uniformly distributed points, and the corresponding first three formant frequencies are calculated. These formants define an acoustic space onto which the articulatory space maps. In the next step, an independent component analysis technique is used to determine acoustic and articulatory coordinate systems whose components are as independent as possible. Finally, using singular value decomposition, acoustic and articulatory coordinate systems are rotated so that each of the first three components of the articulatory space has major influence on one, and only one, component of the acoustic space. An example showing how the proposed model can be applied to the solution of the articulatory-to-acoustic inverse problem is given at the end of the paper.

A new neural network for locating a source by integrating data from a number of sensors is considered. The network gives a solution for inverse problems using a back-propagation algorithm with the architecture to get the solution in the inter-layer weights in a coded form Three different physical quantities are applied to the network, since the scheme has three independent ports; an input port, a tutorial port and an answer port. Our architecture is useful to estimate z" in the problem whose structure is y=f(x,z) where y is the observed data, x is the sensor position and z is the source location. The network integrates the information obtained from a number of sensors and estimates the location of the source. We apply the network to two problems of location estimation: the localization of the active nerves from their evoked potential waveforms and the localization of objects from their echoes using an active sonar system.

A novel method of multichannel surface EMG processing has been developed to compensate for the distortion in bipolar surface EMG signals due to the movement of innervation zones. The distortion of bipolar surface EMG signals was mathematically described as a filtering function. A compensating technique for such distorted bipolar surface EMG signals was developed for the brachial biceps during dynamic contractions in which the muscle length and tension change. The technique is based on multichannel surface EMG measurement, a method for estimating the movement of an innervation zone, and the inverse filtering technique. As a result, the distorted EMG signals were compensated and transformed into nearly identical waveforms, independent of the movement of the innervation zone.

This letter presents a new design method for approximate inverse systems using all-pass networks. The efficacy of approximate inverse systems for input and parameter estimation of nonminimum phase systems is well recognized. in the previous methods, only time domain design of FIR (finite impulse response) type approximate inverse systems were considered. Here, we demonstrate that IIR (infinite impulse response) type approximate inverse systems outperform the previous methods. A nonlinear optimization technique is adopted for designing the proposed system in the frequency domain. Numerical examples are also presented to show the effectiveness of the proposed method.

In this paper we propose a new method for removing the characteristic of the piezoelectric transducer from the received signal in the pulse-echo method so that the time resolution in the determination of transit time of ultrasound in a thin layer is increased. The total characteristic of the pulse-echo system is described by cascade of distributed-constant systems for the ultrasonic transducer, matching layer, and acoustic medium. The input impedance is estimated by the inverse matrix of the cascade system and the voltage signal at the electrical port. From the inverse Fourier transform of input impedance, the transit time in a thin layer object is accurately determined with high time resolution. The principle of the method is confirmed by simulation experiments.

Microwave radiometry has been investigated for non-invasive measurement of temperature in human body. Recent trends are to explore the capability of retrieving a temperature profile or map from a set of brightness temperatures measured by a multifrequency radiometer operating in a 1-6GHz range. The retrieval of temperature from the multifrequency measurement data is formulated as an inverse problem in which the number of independent measurement or data is limited (7) and the data suffer from considerably large random fluctuations. The standard deviation of the data fluctuation is given by the brightness temperature resolution of the instrument (0.04-0.1K). Solutions are prone to instabilities and large errors unless proper solution methods are used. Solution methods developed during the last few years are reviewed: singular system analysis, bio-heat transfer solution matched with radiometric data, and model-fitting combined with Monte Carlo technique. Typical results obtained by these methods are presented to indicate a crosssection of the present-state-of-the-development in the field. This review concludes with discussions on the radiometric weighting function which connects physical temperatures in object to the brightness temperature. Three-dimensional weighting functions derived by the modal analysis and the FDTD method for a rectangular waveguide antenna coupled to a four layered lossy medium are discussed. Development of temperature retrieval procedures incorporating the 3-D weighting functions is an important and challenging task for future work in this field.

This paper describes a SQUID magnetometer and the measurement of small signals. It also describes the current state of SQUID technology developed in the SSL project.

The potential attenuation process of charged human body (HB) is analyzed. A two-dimensional circuit model is presented for predicting the potential attenuation characteristics of the HB charged on the floor. The theoretical equation for the HB potential is derived in the closed form in the Laplacian transformation domain, and the numerical inverse Laplace transform is used to compute it. The half-life or relaxation time of the HB potential for decay is numerically examined with respect to the electrical parameters of shoes. The experiment is also conducted for verifying the validity of the computed result.

For estimating the radiated emission from a metallic enclosure, the authors have developed a numerical computational method which applied inverse analysis. A metallic enclosure containing a loop antenna was set up to be a model source for the numerical analysis. Magnetic fields around the enclosure were measured by measurement systems fabricated in the authors' laboratory. Using the measured magnetic fields, current distributions on the enclosure surface were determined by means of an inverse analysis utilizing the least squares method. From this surface current distribution, the electromagnetic field distributions were estimated by forward analysis on a cylindrical surface 3.0m in radius. The amount of the error in the estimated fields distribution was also discussed.

We present a novel algorithm to reconstruct the refractive-index profile of a circularly symmetric object from measurements of the electromagnetic field scattered when the object is illuminated by a plane wave. The reconstruction algorithm is besed on an iterative procedure of matching the scattered field calculated from a certain refractive-index distribution with the measured scattered field on the boundary of the object. In order to estimate the convergence of the reconstruction, the mean square error between the calculated and measured scattered fields is introduced. It is shown through reconstructing several examples of lossy dielectric cylinders that the algorithm is quite stable and is applicable to high-contrasty models in situations where the Born approximation is not valid.

A method is presented for reconstructing the surface profile of a perfectly conducting rough surface boundary from the measurements of the scattered far-field. The proposed inversion algorithm is based on the use of the Kirchhoff approximation and in order to determine the surface profile, the Fletcher-Powell optimization procedure is applied. A number of numerical results illustrating the method are presented.

A noninvasive method for measuring complex permittivity of biological tissues is proposed. The noninvasive method is based on an inverse scattering technique which employs an iterative procedure. The iterative procedure consists of solving an electric field integral equation using the method of moments and minimizing the square difference between calculated and measured scattered fields. Implementation of the noninvasive method requires the knowledge of the target shape, the incident and measured scattered fields. Based on the noninvasive method, a measuring system of complex permittivity is developed and its reliability is verified.

A pseudoinverse rule, one of major rule to determine a weight matrix for associative memory, has large capacity comparing with other determining rules. However, it is wellknown that the rule has small domains of attraction of memory vectors on account of many spurious states. In this paper, we try to improve the problem by means of subtracting a constant from all diagonal elements of a weight matrix. By this method, many spurious states disappear and eigenvectors with negative eigenvalues are introduced for the orthocomplement of the subspace spanned by memory vectors. This method can be applied to two types of networks: binary network and analog network. Some computer simulations are performed for both two models. The results of the simulations show our improvement is effective to extend error correcting ability for both networks.

The invariant imbedding method combined with the time domain wave splitting technique is applied to the inverse problem for the telegraph equation t2u=(1/r)(pu)-btu+qu in a stratified half-space. The zeroth, second and fourth moments of the 3-D fields are used to reduce the three-dimensional problem to a set of one-dimensional problems. The imbedding equations for R0, R2 and R4, respectively the zeroth, second and fourth moments of the reflection operator, are derived. Numerical results for the reconstruction are presented using the reflection data on the surface.

The inverse problem we consider in this paper seeks, based on the equivalent source method, to determine the shape of perfectly conducting cylinders from the scattered farfield data obtained by using several incident waves. When incident waves of different frequencies are used, the shape of the scatterer can be reconstructed by employing only a few number of observation points. In the reconstruction problem, to determine the shape of the scatterer, the conjugate gradients method is applied. The general approach is applicable to cylindrical scatterers of arbitrary shape. Results of numerical simulations are presented to support the suggested approach.

Reflection mode diffraction tomography is expected to reconstruct a higher resolution image than transmission mode. Its image reconstruction problem, however, in the many cases of practical uses becomes ill-posed one. In this paper, a new reconstruction method of limited angle reflection mode diffraction tomography using maximum entropy method is proposed. Results of simulation showed that the method was able to reconstruct the better quality images than IR method poposed by Kak, et al.

An efficient reconstruction algorithm for diffraction tomography based on the modified Newton-Kantorovich method is presented and numerically studies. With the Fréchet derivative obtained for the Helmholtz equation, one can derive an iterative formula for getting an object function, which is a function of refractive index of a scatterer. Setting an initial guess of the object function to zero, the pth estimate of the function is obtained by performing the inverse Fourier transform of its spectrum. Since the spectrum is bandlimited within a low-frequency band, the algorithm does not require usual regularization techniques to circumvent ill-posedness of the problem. For numerical calculation of the direct scattering problem, the moment method and the FFT-CG method are utilized. Computer simulations are made for lossless and homogeneous dielectric circular cylinders of various radii and refractive indices. In the iteration process of image reconstruction, the imaginary part of the object function is set to zero with a priori knowledge of the lossless scatterer. Then the convergence behavior of the algorithm remarkably gets improved. From the simulated results, it is seen that the algorithm provides high-quality reconstructed images even for cases where the first-order Born approximation breaks down. Furthermore, the results demonstrate fast convergence properties of the iterative procedure. In particular, we can successfully reconstruct the cylinder of radius 1 wavelength and refractive index that differs by 10% from the surrounding medium. The proposed algorithm is also effective for an object of larger radius.

The realization of acoustic inverse filter is often difficult because of the non-minimum phase property and the long time duration of the impulse response of the acoustic enclosure. However, if the signals are divided into a large number of sub-bands, many of the sub-bands are found to be invertible. The invertibility of a sub-band signal depends on the zero distribution of the transfer function in the z-plane. In a multi-microphone system, the transfer functions between the sound source and the mirophones have different zero distributions. The method proposed here, taking advantage of the differences of zero distributions, selects the best invertible microphone in each sub-band, and reconstructs the full band signal by summing up the inverse filtered sub-band signals of the best microphones. The quality of the dereverberated signal using the proposed inverse filtering approach is improved with increasing number of microphones and sub-bands. When seven microphones are used and the number of sub-bands is 513, the quality of the dereverberated speech signals are almost the same with the original ones even when the revergeration time is about one second. The introduction of multi-microphones in addition to sub-band processing provides a new way of dealing with the non-minimum phase problem in deconvolution.