Baker, C. R. (Charles R.) 1932
Overview
Works:  26 works in 44 publications in 2 languages and 391 library holdings 

Genres:  Conference papers and proceedings History 
Roles:  Editor, Author, Other 
Publication Timeline
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Most widely held works about
C. R Baker
 "Hurn House", New Walk : three days' sale : most attractive antique and modern furniture : being the entire contents of the house : the antique items include ... oil paintings ... water colours ... which B.L. Wells & Son, F.A.I., will sell by auction on the premises on ... 28th, 29th and 30th April, 1954 by C. R Baker( Book )
 Baker, C.R by Mary Sayre Haverstock( )
Most widely held works by
C. R Baker
Stochastic processes in underwater acoustics by
C. R Baker(
Book
)
14 editions published between 1986 and 2006 in English and German and held by 294 WorldCat member libraries worldwide
14 editions published between 1986 and 2006 in English and German and held by 294 WorldCat member libraries worldwide
A souvenir history of ye old town of Salem, Ohio, with some pictures and brief references to ye people and things of ye olden
time by
Salem (Ohio)(
Book
)
2 editions published in 1906 in English and held by 58 WorldCat member libraries worldwide
2 editions published in 1906 in English and held by 58 WorldCat member libraries worldwide
Stochastic processes in underwater acoustics : collection of research papers, presented in two invited sessions at the 1985
IEEE(
Book
)
3 editions published in 1986 in English and held by 13 WorldCat member libraries worldwide
3 editions published in 1986 in English and held by 13 WorldCat member libraries worldwide
Economics of hydrogen production and liquefaction updated to 1980 by
C. R Baker(
Book
)
3 editions published in 1979 in English and held by 3 WorldCat member libraries worldwide
3 editions published in 1979 in English and held by 3 WorldCat member libraries worldwide
Lease financing, a practical guide by
C. Richard Baker(
Book
)
1 edition published in 1981 in Undetermined and held by 2 WorldCat member libraries worldwide
Gives the details on legal implications, saleleasebacks in real estate, accounting, and project finance
1 edition published in 1981 in Undetermined and held by 2 WorldCat member libraries worldwide
Gives the details on legal implications, saleleasebacks in real estate, accounting, and project finance
Some Relations between Signal Detection and the Capacity of Communication Channels(
Book
)
1 edition published in 1988 in English and held by 1 WorldCat member library worldwide
The theme of the ComCon conferences is the unification of communications and control. Thus, methods and results that are common to the two areas are of central interest. This paper contains a discussion of a topic that is in this general spirit: relations that exist between signal detection and information theory and/or signal detection. They have bee developed in recent years as a result of specific needs: They have been developed in recent years as a result of specific needs: they are essential in obtaining solutions to channel capacity problems when the noise sample paths comprise an infinitedimensional linear manifold. Channel capacity is one of the most basic problems of information theory. In many setups, such as that of the DMC (discrete memoryless channel), the basic mathematical structure is so simple that measuretheoretic questions do not arise. the situation changes radically when one considers more complicated channels, such as the continuoustime Gaussian channel with memory
1 edition published in 1988 in English and held by 1 WorldCat member library worldwide
The theme of the ComCon conferences is the unification of communications and control. Thus, methods and results that are common to the two areas are of central interest. This paper contains a discussion of a topic that is in this general spirit: relations that exist between signal detection and information theory and/or signal detection. They have bee developed in recent years as a result of specific needs: They have been developed in recent years as a result of specific needs: they are essential in obtaining solutions to channel capacity problems when the noise sample paths comprise an infinitedimensional linear manifold. Channel capacity is one of the most basic problems of information theory. In many setups, such as that of the DMC (discrete memoryless channel), the basic mathematical structure is so simple that measuretheoretic questions do not arise. the situation changes radically when one considers more complicated channels, such as the continuoustime Gaussian channel with memory
Information Capacity of the Matched Gaussian Channel with Jamming. I. FiniteDimensional Channel(
Book
)
1 edition published in 1989 in English and held by 1 WorldCat member library worldwide
Information capacity is considered for the finitedimensional additive Gaussian channel subject to jamming. The problem is modeled as a zerosum twoperson game with mutual information as payoff function. The jammer does not control the ambient Gaussian noise, which is not assumed negligible. The unique saddle point and saddle value are determined, along the jammer's minimax strategy. Keywords: Information capacity; Additive Gaussian channel; Mutual information; Minimax strategy. (JHD)
1 edition published in 1989 in English and held by 1 WorldCat member library worldwide
Information capacity is considered for the finitedimensional additive Gaussian channel subject to jamming. The problem is modeled as a zerosum twoperson game with mutual information as payoff function. The jammer does not control the ambient Gaussian noise, which is not assumed negligible. The unique saddle point and saddle value are determined, along the jammer's minimax strategy. Keywords: Information capacity; Additive Gaussian channel; Mutual information; Minimax strategy. (JHD)
Algorithms for Optimum Detection of Signals in Gaussian Noise(
)
1 edition published in 1991 in English and held by 1 WorldCat member library worldwide
Algorithms are presented for detection of signals in Gaussian noise. The signals can be Gaussian or nonGaussian. The algorithms are derived from a general solution to the continuoustime problem, and are approximations to the continuoustime likelihood ratio. They do not require knowledge of the probability distributions for the signalplusnoise process, but instead require knowledge (or estimation) of a function. Independent sampling is not assumed. One algorithm is fully adaptive to the signalplusnoise process. The algorithms have the potential of providing significant performance improvements, as compared to classical detection methods, when the signalplusnoise process is broadband (stationary or nonstationary), and particularly when it is nonGaussian
1 edition published in 1991 in English and held by 1 WorldCat member library worldwide
Algorithms are presented for detection of signals in Gaussian noise. The signals can be Gaussian or nonGaussian. The algorithms are derived from a general solution to the continuoustime problem, and are approximations to the continuoustime likelihood ratio. They do not require knowledge of the probability distributions for the signalplusnoise process, but instead require knowledge (or estimation) of a function. Independent sampling is not assumed. One algorithm is fully adaptive to the signalplusnoise process. The algorithms have the potential of providing significant performance improvements, as compared to classical detection methods, when the signalplusnoise process is broadband (stationary or nonstationary), and particularly when it is nonGaussian
A Computational Evaluation of New Detection Algorithms(
)
1 edition published in 1990 in English and held by 1 WorldCat member library worldwide
This paper summarizes results of a computational study of two new signal detection algorithms. The new algorithms have the potential for significantly improving existing detection methods when the signalplusnoise process is broadband (stationary or nonstationary), especially when it is nonGaussian. They require no assumptions on the statistical properties of the signalplusnoise process; instead, they require that the drift function of a diffusion be known or estimated. When this function is known, the new discrete time, algorithms are approximations to the likelihood ratio for the continuous time data under some reasonable assumptions on the data characteristics. These assumptions include that of Gaussian noise, although the computational results indicate that good performance can be obtained when the noise is not Gaussian. The study included comparisons with several reference algorithms, using both simulated and passive sonar data. The new methods gave superior performance despite the use of a very rudimentary procedure for estimating the drift function. NonGaussian signal detection, Likelihood ratios, Passive sonar, Sonar signal processing
1 edition published in 1990 in English and held by 1 WorldCat member library worldwide
This paper summarizes results of a computational study of two new signal detection algorithms. The new algorithms have the potential for significantly improving existing detection methods when the signalplusnoise process is broadband (stationary or nonstationary), especially when it is nonGaussian. They require no assumptions on the statistical properties of the signalplusnoise process; instead, they require that the drift function of a diffusion be known or estimated. When this function is known, the new discrete time, algorithms are approximations to the likelihood ratio for the continuous time data under some reasonable assumptions on the data characteristics. These assumptions include that of Gaussian noise, although the computational results indicate that good performance can be obtained when the noise is not Gaussian. The study included comparisons with several reference algorithms, using both simulated and passive sonar data. The new methods gave superior performance despite the use of a very rudimentary procedure for estimating the drift function. NonGaussian signal detection, Likelihood ratios, Passive sonar, Sonar signal processing
Spectral Multiplicity for SecondOrder Stochastic Processes(
)
1 edition published in 1991 in English and held by 1 WorldCat member library worldwide
The theory of spectral multiplicity for secondorder stochastic processes is developed from first principles. Each of the representations originally obtained by Cramer and by Hida is developed. The HellingerHahn theorem on multiplicity in Hilbert space is obtained as a corollary, instead of being used to provide the representations
1 edition published in 1991 in English and held by 1 WorldCat member library worldwide
The theory of spectral multiplicity for secondorder stochastic processes is developed from first principles. Each of the representations originally obtained by Cramer and by Hida is developed. The HellingerHahn theorem on multiplicity in Hilbert space is obtained as a corollary, instead of being used to provide the representations
Neutral density models for aerospace applications by F. A Marcos(
Book
)
1 edition published in 1994 in English and held by 1 WorldCat member library worldwide
1 edition published in 1994 in English and held by 1 WorldCat member library worldwide
Information Capacity of DimensionLimited Channels(
Book
)
1 edition published in 1989 in English and held by 1 WorldCat member library worldwide
Average information capacity is determined for a class of communication channels containing additive noise. Gaussian noise processes and a large class of nonGaussian processes are included. The constraint on the transmitted signals is given in terms of an increasing family of finite dimensional subspaces. The results apply to the classical discretetime channel and to continuoustime channels with fixed signal duration. Keywords: Coding; Linear operators. (KR)
1 edition published in 1989 in English and held by 1 WorldCat member library worldwide
Average information capacity is determined for a class of communication channels containing additive noise. Gaussian noise processes and a large class of nonGaussian processes are included. The constraint on the transmitted signals is given in terms of an increasing family of finite dimensional subspaces. The results apply to the classical discretetime channel and to continuoustime channels with fixed signal duration. Keywords: Coding; Linear operators. (KR)
LikelihoodRatio Detection of Stochastic Signals(
)
1 edition published in 1989 in English and held by 1 WorldCat member library worldwide
Algorithms are given for the detection of a general stochastic signal imbedded in Gaussian or nonGaussian sphericallyinvariant noise. A summary is given of the theoretical development leading to the algorithms, along with the approximations leading to the algorithms. Adaptive and nonadaptive algorithms are described, along with specific procedures for their implementation
1 edition published in 1989 in English and held by 1 WorldCat member library worldwide
Algorithms are given for the detection of a general stochastic signal imbedded in Gaussian or nonGaussian sphericallyinvariant noise. A summary is given of the theoretical development leading to the algorithms, along with the approximations leading to the algorithms. Adaptive and nonadaptive algorithms are described, along with specific procedures for their implementation
Capacity of the Stationary Gaussian Channel(
Book
)
1 edition published in 1988 in English and held by 1 WorldCat member library worldwide
Information capacity of the stationary Gaussian channel is determined under the assumption that both the channel noise and the constraint are defined by rational spectral densities. The results complement a wellknown result to Holsinger and Gallager. The new results given here show that (1) Attention can be restricted to wide sense stationary signals; (2) The new results for the value of the capacity are complementary (under the assumptions used here) to the result of Holsinger and Gallager; together, these results exhaust all possible values of the capacity; (3) The constraints permitted in obtaining Theorem 3 enable the signal process to use more of the available noise bandwidth than signal processes obeying the constraints of the HolsingerGallager model; if there is freedom to choose the constraint, then the capacity can be increased by using a constraint as in Theorem 3. Information theory
1 edition published in 1988 in English and held by 1 WorldCat member library worldwide
Information capacity of the stationary Gaussian channel is determined under the assumption that both the channel noise and the constraint are defined by rational spectral densities. The results complement a wellknown result to Holsinger and Gallager. The new results given here show that (1) Attention can be restricted to wide sense stationary signals; (2) The new results for the value of the capacity are complementary (under the assumptions used here) to the result of Holsinger and Gallager; together, these results exhaust all possible values of the capacity; (3) The constraints permitted in obtaining Theorem 3 enable the signal process to use more of the available noise bandwidth than signal processes obeying the constraints of the HolsingerGallager model; if there is freedom to choose the constraint, then the capacity can be increased by using a constraint as in Theorem 3. Information theory
Information Capacity of the Stationary Gaussian Channel(
Book
)
1 edition published in 1989 in English and held by 1 WorldCat member library worldwide
The information capacity of the mismatched stationary continuoustime Gaussian channel is determined. The assumptions placed on the signal process are less restrictive than those given in previous treatments. Moreover, the assumptions used may have operational advantages over those used previously. (jhd)
1 edition published in 1989 in English and held by 1 WorldCat member library worldwide
The information capacity of the mismatched stationary continuoustime Gaussian channel is determined. The assumptions placed on the signal process are less restrictive than those given in previous treatments. Moreover, the assumptions used may have operational advantages over those used previously. (jhd)
Analysis, Modeling, and Signal Detection for a Set of Passive Sonar Data(
)
1 edition published in 1992 in English and held by 1 WorldCat member library worldwide
A computational evaluation of a set of singlehydrophone passive sonar data is summarized. Included are results on signal detection, statistical characterization (especially normality vs. nonnormality), and fits to a mixtureofnormals distribution
1 edition published in 1992 in English and held by 1 WorldCat member library worldwide
A computational evaluation of a set of singlehydrophone passive sonar data is summarized. Included are results on signal detection, statistical characterization (especially normality vs. nonnormality), and fits to a mixtureofnormals distribution
Absolute Continuity and Mutual Information for Gaussian Mixtures(
Book
)
1 edition published in 1988 in English and held by 1 WorldCat member library worldwide
Absolute continuity, process representations, and the Shannon information are considered for problems involving a Gaussian mixture process (N sub t), t in (0,1). N(omega, t)=A(omega)G(omega, t) a.e. dP(omega)dt, where (G sub t) is a Gaussian process and A is a positive random variable independent of (G sub t). Let (Y sub t), t in 0,1, be a second process with nu sub Y and nu sub N the measures induced on R0,1 and mu sub Y and mu sub N the measures induced on L20,1 (Y sub t) has paths a.s. in L20.1. The CramerHida spectral representation and an extension of Girsanov's theorem are used to obtain results on absolute continuity (nu sub Y <<nu sub N and mu sub Y <<mu sub N) and likelihood ratio in terms of similar results involving a Gaussian mixture local martingale, for which representations are given. These results are then applied to obtain the Shannon mutual information for a communication channel with feedback having (N sub t) as additive noise. Capacity is obtained for the nofeedback channel, subject to an averageenergy type of constraint. (jhd)
1 edition published in 1988 in English and held by 1 WorldCat member library worldwide
Absolute continuity, process representations, and the Shannon information are considered for problems involving a Gaussian mixture process (N sub t), t in (0,1). N(omega, t)=A(omega)G(omega, t) a.e. dP(omega)dt, where (G sub t) is a Gaussian process and A is a positive random variable independent of (G sub t). Let (Y sub t), t in 0,1, be a second process with nu sub Y and nu sub N the measures induced on R0,1 and mu sub Y and mu sub N the measures induced on L20,1 (Y sub t) has paths a.s. in L20.1. The CramerHida spectral representation and an extension of Girsanov's theorem are used to obtain results on absolute continuity (nu sub Y <<nu sub N and mu sub Y <<mu sub N) and likelihood ratio in terms of similar results involving a Gaussian mixture local martingale, for which representations are given. These results are then applied to obtain the Shannon mutual information for a communication channel with feedback having (N sub t) as additive noise. Capacity is obtained for the nofeedback channel, subject to an averageenergy type of constraint. (jhd)
On the Equivalence of Probability Measures(
Book
)
1 edition published in 1981 in English and held by 1 WorldCat member library worldwide
Signal detection problems are discussed for the case when the noise is Gaussian, but signalplusnoise can be nonGaussian. A likelihood ratio is given. (Author)
1 edition published in 1981 in English and held by 1 WorldCat member library worldwide
Signal detection problems are discussed for the case when the noise is Gaussian, but signalplusnoise can be nonGaussian. A likelihood ratio is given. (Author)
Capacity of Generalized Mismatched Gaussian Channels(
Book
)
1 edition published in 1984 in English and held by 1 WorldCat member library worldwide
Information capacity is determined for a Gaussian communication channel when the constraint is given in terms of a covariance which is different from that of the channel noise
1 edition published in 1984 in English and held by 1 WorldCat member library worldwide
Information capacity is determined for a Gaussian communication channel when the constraint is given in terms of a covariance which is different from that of the channel noise
Capacity of Mismatched Gaussian Channels(
Book
)
1 edition published in 1983 in English and held by 1 WorldCat member library worldwide
The capacity of the Gaussian channel without feedback, subject to a generalized energy constraint, is determined in an earlier document, In that work, the constraint is given in terms of the covariance of the channel noise process. However, these are many situation where one may wish to determine capacity subject to a constraint determined by a covariance that is different form that of the channel noise. An example is in jamming or countermeasures situations. Channels where the covariance of the noise is the same as that of the constraint will be called matched channels; otherwise, we say that the channel is mismatched (to the constraint). In this paper, the capacity of the mismatched Gaussian channel is determined for two situations; the finitedimensional channel, and the infinitedimensional channel with a dimensionality constraint on the space of transmitted signals. Results on the infinitedimensional mismatched channel without a dimensionality constraint on the signal are given elsewhere. Various special cases of the mismatched channel have been treated previously. The results for the mismatched channel differ significantly from those for the matched channel. A discussion of these differences follows the proof of the main result
1 edition published in 1983 in English and held by 1 WorldCat member library worldwide
The capacity of the Gaussian channel without feedback, subject to a generalized energy constraint, is determined in an earlier document, In that work, the constraint is given in terms of the covariance of the channel noise process. However, these are many situation where one may wish to determine capacity subject to a constraint determined by a covariance that is different form that of the channel noise. An example is in jamming or countermeasures situations. Channels where the covariance of the noise is the same as that of the constraint will be called matched channels; otherwise, we say that the channel is mismatched (to the constraint). In this paper, the capacity of the mismatched Gaussian channel is determined for two situations; the finitedimensional channel, and the infinitedimensional channel with a dimensionality constraint on the space of transmitted signals. Results on the infinitedimensional mismatched channel without a dimensionality constraint on the signal are given elsewhere. Various special cases of the mismatched channel have been treated previously. The results for the mismatched channel differ significantly from those for the matched channel. A discussion of these differences follows the proof of the main result
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Related Identities
 McCord, William B. 18441908 Editor
 Salem (Ohio) General Centennial Committee
 Gee, George H.
 NORTH CAROLINA UNIV AT CHAPEL HILL Dept. of STATISTICS
 Gualtierotti, A. F.
 Frey, M. R.
 Chao, I. F.
 IEEE International Symposium on Information Theory (1985 ; Brighton, England)
 Langley Research Center
 Union Carbide Corporation Linde Division
Associated Subjects
ArtPrivate collections Automatic control Calculus of variations Engineering Furniture GasesLiquefaction House furnishings Industrial equipment leases Industrial equipment leasesFinance Liquid hydrogen Mathematical optimization Mechatronics OhioSalem Robotics Stochastic processes System theory Underwater acoustics United States