
	Where results make sense

Topic: Normalising constant

	Multidimensional Scaling (Site not responding. Last check: 2007-10-31)
		A least-squares MDS technique defines a loss function that is a weighted and possibly normalised sum of errors over all pairs of objects (i,j), and thus it penalises the overall approximation error.
		We note that minimising (3.16) is equivalent to minimising (3.13), and we use the normalised form when reporting results.
		k is Boltzmann's constant, and is obviously meaningless in the function minimisation context, thus the whole denominator is replaced by a single parameter t, although the thermal nomenclature is retained.
	www.pavis.org /essay/multidimensional_scaling.html (6876 words)

	Earth 458: Physical Hydrogeology
		Note that this equation is really a statement of hydraulic equilibrium - that is, the total energy per unit weight (the total head, h) at any point within the region of flow is constant.
		Normalising to m yields the Bernoulli equation: E
		Normalising to mg is the same as normalising to unit weight of water.
	www.rpi.edu /~abrajt/Hydrocycle.html (832 words)

	C:\USER\LECTURES\BIOMED5.DOC
		The wave propagates with constant velocity, c, and with constant attenuation per unit distance travelled, a.
		In older machines the data may be acquired by linearly moving the transducer at a constant velocity across the patient in the line of the section required (Figure 217).
		The reflectivity R(x,y,z) is assumed to remain constant throughout the scan as it is assumed that there is little or no motion of body tissues.
	www.eelab.usyd.edu.au /ELEC3801/notes/ultrasonic_imaging.htm (3303 words)

	Faculty of Engineering
		This approach is used for estimating the unknown normalising constant for a particular parametric spatial point process for a grid of parameter values.
		Simulation of the posterior is done using a Metropolis-Hastings algorithm involving ratios of unknown normalising constants.
		Using a Metropolis-Hastings algorithm for posterior simulation often involves a ratio of unknown normalising constants in the Hastings ratio.
	auaw2.aua.auc.dk /fak-tekn/phd/diss0304/abstracts/bertelsen.htm (457 words)

	UNIVERSITY OF GLASGOW (Site not responding. Last check: 2007-10-31)
		Approaches to normalising constant calculation for autologistic type models and use in statistical modelling
		Unfortunately the distribution generally remains incompletely specified as the normalising constant is generally computationally complex to compute.
		From this we can begin to determine what factors drive their decision to move so as to better understand the Scottish grey seal population, which, in turn, enables to manage and protect these populations more effectively.
	www.stats.gla.ac.uk /~ernst/Seminars/dept_seminars.html (520 words)

	11.3 Monte Carlo Methods
		As can be seen from the graph, the average is almost constant from the start, as it should, because of unbiasedness, while the range decreases very slowly, as it should, because of extreme value theory.
		In fact, in most cases, two different samples have to be used, if only because the support of the importance distribution for the numerator is not the whole space, unless, of course, all normalising constants are known.
		Specific Monte Carlo methods for the estimation of ratios of normalizing constants, or, equivalently, of Bayes factors, have been developed in the past five years.
	www.quantlet.com /mdstat/scripts/csa/html/node190.html (1723 words)

	Apparatus incorporating recursive estimators
		Here c.sub.y is a normalising constant, while L.sub.y (x) is called the likelihood function for x generated by the observation y.
		Here c.sub.y is a normalising constant, f(x) is the probability density function for aircraft position prior to the TCN update, while f(x.vertline.y) is the density function after taking into account a set y of TCN measurement data as described above.
		It is also permissible at this stage to apply (or remove) a constant scale factor, since the effect of this will be negated in any case by the normalising constant c.sub.y in equation (1.4).
	www.freepatentsonline.com /4786908.html (8483 words)

	DANotes: Motors: Acceleration and periodic loads
		Since motor speed is essentially constant, power may be substituted for torque here.
		It is evident from a free body of the coupling running at steady speed, that the torque must be constant across it.
		A special form of hydraulic coupling, with an adjustable scoop for altering the amount of oil, is used as a variable speed device.
	www.mech.uwa.edu.au /DANotes/motors/unsteady/unsteady.html (1534 words)

	An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants -- Møller ...
		An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants -- Møller et al.
		normalising constant which is also a function of that parameter.
		Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues.
	biomet.oxfordjournals.org /cgi/content/short/93/2/451?rss=1 (241 words)

	SFB386: Abstracts 2003
		Norming constants are obtained and it is shown that the considered processes exhibit the same extremal behavior as their associated iid sequences.
		To this end a piecewise exponential model utilizing piecewise constant hazard rates and a Poisson model were devised.
		In the case of a dichotomous explanatory variable x the magnitude of the bias is strongly influenced by the baseline risk defined by the constants of the models and the risk resulting for the high risk group.
	www.stat.uni-muenchen.de /sfb386/papers/abs2003.html (8945 words)

	8. STOCHASTIC MODELS FOR PREDICTION OF THE CATCH DYNAMICS
		are unknown amplitudes, and G is an unknown static shift constant.
		Other methods can also be used to test model (5), such as the usual statistical criteria to test whether the residual signal e(t) is Gaussian white noise or more sophisticated tools such as the AIC (Akaike Informational Criterion) to decide upon which terms to include (Kashyap and Rao 1976).
		The Gaussian probability distribution, also known as the Normal distribution, is often appropriate when errors show constant variation.
	www.fao.org /docrep/005/y2787e/y2787e09.htm (2360 words)

	ATNORM - Normalises model atmosphere fluxes (Site not responding. Last check: 2007-10-31)
		The angular diameter implied by the normalising constant is printed at the terminal.
		The normalised fluxes are left in the `current' arrays, and are plotted if mode=1 (the default).
		In this case, the Y values plotted (and left in the `current' arrays) are logs of the normalised model atmosphere fluxes; however, the unnormalised atmosphere data in the `current' arrays MUST be linear in Y to start off with (i.e.
	www.starlink.rl.ac.uk /star/docs/sun50.htx/node52.html (170 words)

	CMG-5T triaxial accelerometer (Site not responding. Last check: 2007-10-31)
		A, a constant which is evaluated to make A × H (s) dimensionless and with a value of 1 over the flat portion of the frequency response.
		In practice, it is possible to design a system transfer function with a very wide-range flat frequency response.
		The normalising constant A is calculated at a normalising frequency value fm = 1 Hz, with s = j fm, where j = √–1.
	www.guralp.net /support/manuals/5T/s.cmg5ttriaxialaccelerometer.insidethe5t.usingthesensortransferfunction.html (302 words)

	::: PGET ::: : : Cadernos de Tradução
		Thus, terminology is a discipline which identifies the vocabulary related to a determined speciality in a systematic way, analysing the vocabulary and, if necessary, creating and normalising it in order to attend the needs of users' expression.
		In this sense, the use of borrowings in this area is seen as justifiable as it guarantees the identification of specific terms related to certain domains of knowledge.
		As information is exposed much faster nowadays, "rewriting becomes a constant activity; there are no singular ST and no definitive TT; globalisation has effectively blown apart most of the models we use to think about translation and indeed communication" (ibid.: 221).
	www.cadernos.ufsc.br /online/8/sinara.htm (4301 words)

	Astron. Astrophys. 354, 802-814 (2000)
		and normalising constant A of IMF in all observed SFCs were derived.
		is the value of the normalising constant estimated from Eq.
		where constant A is estimated from the integral IMF in a galaxy plotted in Fig.
	aa.springer.de /papers/0354003/2300802/sc7.htm (846 words)

	[No title]
		This enables them to be efficiently calculated from the $F$s, using either linear regression to fit the intensities as a function of resolution or to scale the $\leftF\right^2$ in resolution ``shells''.
		Normalised structure factors are heavily used in direct methods calculations.
		This can be represented by the Hendrickson and LAttman distribution: \begin{equation} \label{eq:hendlatt} P(\phi)=N\exp(A\cos(\phi)+B\sin(\phi)+C\cos(2\phi)+D\cos(2\phi)) \end{equation} where $N$ is a normalising constant, $\phi$ is the phase assuming that the distribution is centred about zero, and $A$,$B$,$C$ and $D$ are constants known as the \emph{Hendrickson-Lattman coefficients}.
	www-users.york.ac.uk /~rwg3/Reynolds_thesis/chapter1.tex (3384 words)

	Loudness (Site not responding. Last check: 2007-10-31)
		I thought this was a bad thing and therefore suggested that each wavetable should have the same RMS value.
		Therefore, the riches wavetable should be normalised and all the rest should be multiplied by the same normalising factor so the harmonics have the same amplitude.
		> > Keeping a constant amplitude of the harmonics is the antithesis of what is > wanted as the lower the note, the louder it becomes (more than simply > normalising it).
	shoko.calarts.edu /pipermail/music-dsp/1999-November/003090.html (388 words)

	IStVaN — Invariant Set Variants for Normalisation
		a set of genes with no or little difference in actual expression levels, from a set of pairs of microarray measured expression levels, and for inferring normalising functions based on a set of pairwise data, possibly an invariant set determined by one of the implemented methods.
		Polynomials – the data is fitted by the polynomial of constant degree d that minimises the (weighted) sum of squared deviations to the data set
		Plots of data points and inferred normalising functions from one run of our experiment is also available.
	www.brics.dk /~rlyngsoe/istvan (541 words)

	Web Site for Perfectly Random Sampling with Markov Chains:
		It gives a universal randomized stationary stopping time that is within a constant factor of optimal, and another algorithm that is faster when the Markov chain can be simulated starting from any state rather than just observed in action.
		Surprisingly, both algorithms are intimately related to the generation of random spanning trees of a weighted directed graph, and this paper gives tree algorithms that are both faster and more general than the Broder/Aldous algorithm.
		The proportionality constant is given and is easily calculated.
	dimacs.rutgers.edu /~dbwilson/exact.html (14686 words)

	Web Site for Perfectly Random Sampling with Markov Chains:
		It gives a universal randomized stationary stopping time that is within a constant factor of optimal, and another algorithm that is faster when the Markov chain can be simulated starting from any state rather than just observed in action.
		Surprisingly, both algorithms are intimately related to the generation of random spanning trees of a weighted directed graph, and this paper gives tree algorithms that are both faster and more general than the Broder/Aldous algorithm.
		The same difficulty arises in computer science problems where one seeks to sample randomly from a large finite distributive lattice whose precise size cannot be ascertained in any reasonable amount of time.
	dbwilson.com /exact (14686 words)

	The Spatial Distribution of Lineation Length
		Normalising the data to form a probability distribution,
		Substituting (7.4) and (7.7) into (7.2) allows the theoretical distribution to be calculated and compared with a percentage frequency histogram using bin-width dx and with known mean and variance.
		where l is the lineation length and N is the cumulative number of values >= l, c is a normalising constant and D is the exponent.
	bluesofa.mysite.wanadoo-members.co.uk /PhD/node73.htm (2342 words)

	Lecture 19: Bayesian Inference in Vision
		Usually, there is uncertainty in the features that we extract from the image, and this poses a problem in how to associate the prior knowledge with what we extract.
		When we looked at active contours, we saw that the segmentation could be regarded as an optimisation on the position of the boundary, and that by setting the heuristic constants in the energy equation, we could make the snake behave differently, either following the contour in detail or smoothing it out and filling gaps.
		For example, in extracting a wheel using the Hough transform, we could use summed gradient magnitudes of the voting pixels (normalised to the circumference) as a measure of how good the wheel really was.
	www.doc.ic.ac.uk /~dfg/vision/v19.html (1477 words)

	Friel (Site not responding. Last check: 2007-10-31)
		"Calculating the normalisation constant for the autologistic distribution and related distributions"
		is to describe some recent methods to calculate the normalising
		constant using both an exact analytic method together with
	www.bath.ac.uk /%7Emassch/Seminars/Formal/2002-2003/Friel.htm (85 words)

	Estimating the expectation of macrovariables (Site not responding. Last check: 2007-10-31)
		It is important to keep in mind that it is the lack of knowledge of the normalising constant of
		This will have important consequences for the task of estimating the FEDs (see section 2.4.3).
		1.32 essentially arises from the lack of knowledge of the relative normalisation constants of
	www.ph.ed.ac.uk /~arjun/arjun_thesis/node18.html (693 words)

	Liangqun Li's Homepage (Site not responding. Last check: 2007-10-31)
		Sequential Monte Carlo (SMC) methods are a set of flexible simulation-based methods for sampling from a sequence of probability distributions; each distribution being only known up to a normalising constant.
		These methods were originally introduced in the early 50's by physicists and have become very popular over the past few years in statistics and related fields.
		Much research is therefore devoted to the design of efficient sampling strategies in order to sample particles in regions of high probability mass.
	see.xidian.edu.cn /graduate/lqli/Research.htm (177 words)

	[E-medd] Ph.D. Defence by Kasper K. Berthelsen, Aalborg University (Site not responding. Last check: 2007-10-31)
		These point processes are specified by a density, which typically does not have a known normalising constant, making inference difficult.
		We consider how to approximate ratios of unknown normalising constants using a combination of perfect simulation and path sampling.
		Further, we investigate an auxiliary variable method, which avoids ratios of unknown normalising constants.
	www.dsts.dk /pipermail/e-medd/2003-November/000017.html (345 words)

	Aileen Kennedy BA(Hons) in Photography (Site not responding. Last check: 2007-10-31)
		A familiar setting, however contrived, has succeeded in "normalising" the surreal custom of waking.
		I have attempted to capture our sense of waiting by focusing on the backdrop to our funeral traditions.
		While we move through this cycle, the setting remains constant.
	www.kst.dit.ie /dit/photo/exhib1/ak0.html (71 words)

	Ettekanne
		Analysis of various geometric models has shown that if superclusters form a quasiregular lattice with an almost constant step size then the cluster correlation function is oscillating, it has alternate secondary maxima and minima, separated by half the period of oscillations.
		The cosmic variance depends on the number of clusters in samples and does not depend on the bin size, the normalising constant was determined from the scatter of realisations of various N-body and geometric models (for details see Einasto et al.
		Four initial spectra were used, corresponding to the standard CDM scenario with Omega(0)=1 and Hubble constant h=0.5, a CDM model with cosmological constant (Omega(Lambda)=0.7, Omega(0)=0.3), a double power-law model with spectral index n=1 on large scales, and index n=-1.5 on small scales, and a transition at scale Lambda(t)=128 h
	www.aai.ee /~einasto/cosm.html (3076 words)

	noisy OR for non-boolean variables (Site not responding. Last check: 2007-10-31)
		Therefore the noisy OR rule gives a possibility for the presence of X if at least one of the U's is present there also.
		The relation ignores noise, and F(U) is a normalising constant to make the thing integrate over x to unity.
		This works if p(XU) can be decomposed into the U_i contributions, but the normalising factor is still a joint function of all the U_i's.
	www.cleverset.com /advanced_r_and_d/archive/2002/msg00114.html (423 words)

	[No title]
		MCMC is a technique for sampling from space that might be difficult to sample from because it does not have an analytical form or it may be difficult to integrate, in which case a normalising constant and a probability density function (pdf) cannot be found.
		The elements might be a numerical result from Monte Carlo sampling within a multivariate system, which can not be sampled directly, but are generated from other sampled variables.
		Consequently, the second important property of MCMC samplers is that the probability of a state need never be known to better than a normalising constant.
	members.lycos.co.uk /hugtenburg/normexp/normexp_sampler.html (1202 words)

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