Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169695
M. El-Gabali, M. Shridhar, M. Ahmadi
Restoration of noisy images through the use of a Gibbs field model for the image and a Gaussian random field characterization of the corrupting noise is discussed in this paper. Two new algorithms capable of parallel implementation are presented and shown to yield satisfactory restoration of images corrupted by high levels of noise.
{"title":"Segmentation of noisy images modelled by Markov random fields with Gibbs distribution","authors":"M. El-Gabali, M. Shridhar, M. Ahmadi","doi":"10.1109/ICASSP.1987.1169695","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169695","url":null,"abstract":"Restoration of noisy images through the use of a Gibbs field model for the image and a Gaussian random field characterization of the corrupting noise is discussed in this paper. Two new algorithms capable of parallel implementation are presented and shown to yield satisfactory restoration of images corrupted by high levels of noise.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132392076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169657
D. Slock, J. Cioffi, T. Kailath
The important problem of Adaptive Line Enhancing (ALE) is addressed in this paper. Its solution involves an Adaptive Notch Filter (ANF) proposed in [1],[2] using a minimal parameter constrained infinite impulse response (IIR) model in conjunction with the Recursive Prediction Error Method (RPEM) [3]. A Fast Transversal Filter (FTF) algorithm for the adaptive RLS-type updating of the linear phase filter is presented.
{"title":"A fast transversal filter for adaptive line enhancement","authors":"D. Slock, J. Cioffi, T. Kailath","doi":"10.1109/ICASSP.1987.1169657","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169657","url":null,"abstract":"The important problem of Adaptive Line Enhancing (ALE) is addressed in this paper. Its solution involves an Adaptive Notch Filter (ANF) proposed in [1],[2] using a minimal parameter constrained infinite impulse response (IIR) model in conjunction with the Recursive Prediction Error Method (RPEM) [3]. A Fast Transversal Filter (FTF) algorithm for the adaptive RLS-type updating of the linear phase filter is presented.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134424551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169743
H. Hung, M. Kaveh
In this paper we investigate the degee of sufficiency of the approximately coherently averaged covariance matrix [1] via a relative efficiency measure, termed the Relative Information Index (RII) [2], for the estimation of the parameters of multiple wideband sources. First, we prove that all the narrowband sample covariance matrices are minimal sufficient under the asymptotic normality condition of the raw data samples. The asymptotic distribution and its associated first- and second-order statistics of the approximately coherently averaged covariance matrix [1] are derived. The Fisher's Information matrices of the statistic and the raw data are then evaluated for the computation of the RII's.
在本文中，我们通过一种称为相对信息指数(relative Information Index, RII)[2]的相对效率度量来研究近似相干平均协方差矩阵[1]的充分性程度，用于估计多个宽带源的参数。首先，我们证明了在原始数据样本的渐近正态性条件下，所有窄带样本协方差矩阵都是最小充分的。导出了近似相干平均协方差矩阵的渐近分布及其相关的一阶和二阶统计量[1]。然后对统计数据和原始数据的费雪信息矩阵进行评估，以计算RII。
{"title":"On the statistical sufficiency of the coherently averaged covariance matrix for the estimation of the parameters of wideband sources","authors":"H. Hung, M. Kaveh","doi":"10.1109/ICASSP.1987.1169743","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169743","url":null,"abstract":"In this paper we investigate the degee of sufficiency of the approximately coherently averaged covariance matrix [1] via a relative efficiency measure, termed the Relative Information Index (RII) [2], for the estimation of the parameters of multiple wideband sources. First, we prove that all the narrowband sample covariance matrices are minimal sufficient under the asymptotic normality condition of the raw data samples. The asymptotic distribution and its associated first- and second-order statistics of the approximately coherently averaged covariance matrix [1] are derived. The Fisher's Information matrices of the statistic and the raw data are then evaluated for the computation of the RII's.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130893342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169320
D. Linebarger, D. Johnson
The fundamental signal model for narrowband direction finding - the propagation of several sinusoidal planar wavefronts in a medium containing an array of sensors with additive Gaussian noise present - is assumed implicitly in most high resolution beamforming algorithms. The "natural" parameters for this problem - angles of arrival, signal strengths, inter-signal coherences, and noise strength - specify entirely the statistic used by many algorithms, the spatial correlation matrixR. Combining the relevant parameters for a given situation in a parameter vector p, an estimate of the true parameter vector can be obtained as the solution of an optimization problem:min{hat{p}}max{min}parallelhat{R} - R(hat{p})parallelwherehat{R}is an estimate ofR. The minimizinghat{p}yields direct estimates of the relevant parameters rather than extracting them from an intermediate quantity such as a beampattern. This parametric method is an unbiased estimator which is capable of resolving closely spaced, completely coherent sources at low signal to noise ratios and low time-bandwidth product.
{"title":"A parametric direction finding technique","authors":"D. Linebarger, D. Johnson","doi":"10.1109/ICASSP.1987.1169320","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169320","url":null,"abstract":"The fundamental signal model for narrowband direction finding - the propagation of several sinusoidal planar wavefronts in a medium containing an array of sensors with additive Gaussian noise present - is assumed implicitly in most high resolution beamforming algorithms. The \"natural\" parameters for this problem - angles of arrival, signal strengths, inter-signal coherences, and noise strength - specify entirely the statistic used by many algorithms, the spatial correlation matrixR. Combining the relevant parameters for a given situation in a parameter vector p, an estimate of the true parameter vector can be obtained as the solution of an optimization problem:min{hat{p}}max{min}parallelhat{R} - R(hat{p})parallelwherehat{R}is an estimate ofR. The minimizinghat{p}yields direct estimates of the relevant parameters rather than extracting them from an intermediate quantity such as a beampattern. This parametric method is an unbiased estimator which is capable of resolving closely spaced, completely coherent sources at low signal to noise ratios and low time-bandwidth product.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127899777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169402
B. Paillard, J. Soumagne, P. Mabilleau, S. Morissette
The following paper discusses a vectorial description of the subband decomposition/ reconstruction process and shows its advantages compared to the usual description. The following points are examined:bulletnecessary and sufficient conditions for exact reconstruction,bulletreconstruction error measure,bulletinteresting properties of exact reconstruction processes, and comparison between transform coding and subband coding.
{"title":"Filters for subband coding analytical approach","authors":"B. Paillard, J. Soumagne, P. Mabilleau, S. Morissette","doi":"10.1109/ICASSP.1987.1169402","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169402","url":null,"abstract":"The following paper discusses a vectorial description of the subband decomposition/ reconstruction process and shows its advantages compared to the usual description. The following points are examined:bulletnecessary and sufficient conditions for exact reconstruction,bulletreconstruction error measure,bulletinteresting properties of exact reconstruction processes, and comparison between transform coding and subband coding.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114821243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169679
S. Shaw, R. Figueiredo
Waveforms may be represented symbolically such that their underlying, global structural composition is emphasized. One such symbolic representation is the relational tree. The relational tree is a computer data structure that describes the relative size and placement of peaks and valleys in a waveform. Researchers have developed various distance measures which serve as tree metrics. A tree metric defines a tree space. We are able to cluster groups of trees by their proximity in a tree space. Linear discriminants are used to reduce vector space dimensionality and to improve cluster performance. A tree transformation operating on a regular tree language accomplishes this same goal in a tree space. Under certain restrictions, relational trees form a regular tree language. Combining these concepts yields a waveform recognition system. This system recognizes waveforms even when they have undergone a monotonic transformation of the time axis. The system performs well with high signal to noise ratios, but further refinements are necessary for a working waveform interpretation system.
{"title":"Structural processing of waveforms as trees","authors":"S. Shaw, R. Figueiredo","doi":"10.1109/ICASSP.1987.1169679","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169679","url":null,"abstract":"Waveforms may be represented symbolically such that their underlying, global structural composition is emphasized. One such symbolic representation is the relational tree. The relational tree is a computer data structure that describes the relative size and placement of peaks and valleys in a waveform. Researchers have developed various distance measures which serve as tree metrics. A tree metric defines a tree space. We are able to cluster groups of trees by their proximity in a tree space. Linear discriminants are used to reduce vector space dimensionality and to improve cluster performance. A tree transformation operating on a regular tree language accomplishes this same goal in a tree space. Under certain restrictions, relational trees form a regular tree language. Combining these concepts yields a waveform recognition system. This system recognizes waveforms even when they have undergone a monotonic transformation of the time axis. The system performs well with high signal to noise ratios, but further refinements are necessary for a working waveform interpretation system.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114622548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169579
F. Soong
In this paper, we propose a complete training procedure for creating a subword-based network and test it in an isolated word recognition experiment. We first hand segment one training token per word into contiguous subword segments with the aid of an interactive program that can display and playback various acoustic features of an utterance. The subword segmental units adopted in this paper consist of four different sound classes including: stationary sounds, fast transitional sounds, slow transitional sounds plus consonant clusters and others. The hand segmented token is used to initialize a subword-based word network which is then refined by using more training tokens. The refinement is carried out with a two-level dynamic programming (DP) procedure. At the first level, or the word level, an endpoint-relaxed DP algorithm is used to remove any possible endpointing errors and to mark tentative segment boundaries. Between the marked segment boundaries, another endpoint-relaxed DP algorithm is employed at the segment level to refine the segments extracted at the word level. A segment-based word network, which consists of serial and parallel branches, is generated from this training procedure. While serial branches are generated by using acoustically similar segments aligned at the segment level parallel branches are created for accomodating different acoustic manifestations of the same sound class in different phonetic contexts or different pronunciations. A speaker-dependent, isolated word, recognition experiment was carried out. For a four-speaker(2 male and 2 female), English alphabet data base, the segment-based network, when compared with a conventional word-template-based approach, gives improved performance. The word error rate is reduced from 11.2% for the word-based recognizer down to 7.7% for the network-based recognizer; or correspondingly, the number of misrecognized words is reduced from 116 to 80 out of 1040 recognition trials.
{"title":"A training procedure for a segment-based-network approach to isolated word recognition","authors":"F. Soong","doi":"10.1109/ICASSP.1987.1169579","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169579","url":null,"abstract":"In this paper, we propose a complete training procedure for creating a subword-based network and test it in an isolated word recognition experiment. We first hand segment one training token per word into contiguous subword segments with the aid of an interactive program that can display and playback various acoustic features of an utterance. The subword segmental units adopted in this paper consist of four different sound classes including: stationary sounds, fast transitional sounds, slow transitional sounds plus consonant clusters and others. The hand segmented token is used to initialize a subword-based word network which is then refined by using more training tokens. The refinement is carried out with a two-level dynamic programming (DP) procedure. At the first level, or the word level, an endpoint-relaxed DP algorithm is used to remove any possible endpointing errors and to mark tentative segment boundaries. Between the marked segment boundaries, another endpoint-relaxed DP algorithm is employed at the segment level to refine the segments extracted at the word level. A segment-based word network, which consists of serial and parallel branches, is generated from this training procedure. While serial branches are generated by using acoustically similar segments aligned at the segment level parallel branches are created for accomodating different acoustic manifestations of the same sound class in different phonetic contexts or different pronunciations. A speaker-dependent, isolated word, recognition experiment was carried out. For a four-speaker(2 male and 2 female), English alphabet data base, the segment-based network, when compared with a conventional word-template-based approach, gives improved performance. The word error rate is reduced from 11.2% for the word-based recognizer down to 7.7% for the network-based recognizer; or correspondingly, the number of misrecognized words is reduced from 116 to 80 out of 1040 recognition trials.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117148404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169489
G. Boudreaux-Bartels, T. Parks
An algorithm for evaluating the Discrete Fourier Transform (DFT) at particular output frequency is derived using a technique called summation by parts (SBP). This technique is shown to reduce the number of multiplications and the number of bits per multiplicative coefficient needed to implement the DFT. For many transform lengths, only two one-bit multiplications or simple memory shifts are needed to implement the DFT. When the DFT length is prime, a SBP algorithm designed for a fixed output frequency index can be used to evaluate the DFT at any other non-zero output frequency index simply by appropriately changing the order of the input sequence.
{"title":"Discrete Fourier transform using summation by parts","authors":"G. Boudreaux-Bartels, T. Parks","doi":"10.1109/ICASSP.1987.1169489","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169489","url":null,"abstract":"An algorithm for evaluating the Discrete Fourier Transform (DFT) at particular output frequency is derived using a technique called summation by parts (SBP). This technique is shown to reduce the number of multiplications and the number of bits per multiplicative coefficient needed to implement the DFT. For many transform lengths, only two one-bit multiplications or simple memory shifts are needed to implement the DFT. When the DFT length is prime, a SBP algorithm designed for a fixed output frequency index can be used to evaluate the DFT at any other non-zero output frequency index simply by appropriately changing the order of the input sequence.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"317 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124488983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169674
J. Abel, J. Smith
The problem of estimating the location of a radiating source from range difference measurements taken from a passive, stationary array is discussed. A new closed-form source location estimator, termed the Spherical Interpolation Estimator, is presented and analyzed. The location estimates produced by the Spherical Interpolation Estimator are approximate minimizers of a weighted equation error norm, and are shown to approach the maximum likelihood source location estimator.
{"title":"The spherical interpolation method for closed-form passive source localization using range difference measurements","authors":"J. Abel, J. Smith","doi":"10.1109/ICASSP.1987.1169674","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169674","url":null,"abstract":"The problem of estimating the location of a radiating source from range difference measurements taken from a passive, stationary array is discussed. A new closed-form source location estimator, termed the Spherical Interpolation Estimator, is presented and analyzed. The location estimates produced by the Spherical Interpolation Estimator are approximate minimizers of a weighted equation error norm, and are shown to approach the maximum likelihood source location estimator.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127373627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1987-04-06DOI: 10.1109/ICASSP.1987.1169608
J. Reimer, P. Lawrence
This paper considers the characterization ofnabla^{2}Gfiltered images by their zero crossings. It has been suggested thatnabla^{2}Gfiltered images might be characterized by their zero crossings [1]. It is shown here thatnabla^{2}Gfiltered images, filtered in 1-D or 2-D are not, in general, uniquely given within a scalar by their zero crossing locations. Two theorems in support of such a suggestion are considered. We consider the differences between the requirements of Logan's theorem andnabla^{2}Gfiltering, and show that the zero crossings which result from these two situations differ significantly in number and location. Logan's theorem is therefore not applicable tonabla^{2}Gfiltered images. A recent theorem by Curtis [8] on the adequacy of zero crossings of 2-D functions is also considered. It is shown that the requirements of Curtis' theorem are not satisfied by allnabla^{2}Gfiltered images. An example of two differentnabla^{2}Gfiltered images with the same zero crossings is presented.
{"title":"Characterizing ∇2G filtered images by their zero crossings","authors":"J. Reimer, P. Lawrence","doi":"10.1109/ICASSP.1987.1169608","DOIUrl":"https://doi.org/10.1109/ICASSP.1987.1169608","url":null,"abstract":"This paper considers the characterization ofnabla^{2}Gfiltered images by their zero crossings. It has been suggested thatnabla^{2}Gfiltered images might be characterized by their zero crossings [1]. It is shown here thatnabla^{2}Gfiltered images, filtered in 1-D or 2-D are not, in general, uniquely given within a scalar by their zero crossing locations. Two theorems in support of such a suggestion are considered. We consider the differences between the requirements of Logan's theorem andnabla^{2}Gfiltering, and show that the zero crossings which result from these two situations differ significantly in number and location. Logan's theorem is therefore not applicable tonabla^{2}Gfiltered images. A recent theorem by Curtis [8] on the adequacy of zero crossings of 2-D functions is also considered. It is shown that the requirements of Curtis' theorem are not satisfied by allnabla^{2}Gfiltered images. An example of two differentnabla^{2}Gfiltered images with the same zero crossings is presented.","PeriodicalId":140810,"journal":{"name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127258766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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