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In mathematics, σ-approximation adjusts a Fourier summation to greatly reduce the Gibbs phenomenon, which would otherwise occur at discontinuities. An
Sigma_approximation
Property of artificial neural networks
In the field of machine learning, the universal approximation theorems (UATs) state that neural networks with a certain structure can, in principle, approximate
Universal approximation theorem
Universal_approximation_theorem
Technique in numerical linear algebra
In mathematics, low-rank approximation refers to the process of approximating a given matrix by a matrix of lower rank. More precisely, it is a minimization
Low-rank_approximation
Technique in signal processing
who named it after Cornelius Lanczos due to Duchon's use of the sigma approximation in constructing the filter, a technique created by Lanczos. The effect
Lanczos_resampling
Approximation in many-body systems
an infinitesimal amount. The GW approximation is then Σ ( 1 , 2 ) ≈ i G ( 1 , 2 ) W ( 1 + , 2 ) {\displaystyle \Sigma (1,2)\approx iG(1,2)W(1^{+},2)}
GW_approximation
Root-finding algorithm
_{2}(1+m_{x})\approx m_{x}+\sigma } where σ {\displaystyle \sigma } is a free parameter used to tune the approximation. For example, σ = 0 {\displaystyle \sigma =0} yields
Fast_inverse_square_root
Measure of variation in statistics
An approximation can be given by replacing N − 1 with N − 1.5, yielding: σ ^ = 1 N − 1.5 ∑ i = 1 N ( x i − x ¯ ) 2 , {\displaystyle {\hat {\sigma }}={\sqrt
Standard_deviation
Method for converting signals between digital and analog
approximation of the input while the quantizer used in delta-sigma must take values outside of the range of the input signal. In general, delta-sigma
Delta-sigma_modulation
Approximations used in machine learning
Low-rank matrix approximations are essential tools in the application of kernel methods to large-scale learning problems. Kernel methods (for instance
Low-rank matrix approximations
Low-rank_matrix_approximations
Probability distribution
{\textstyle \sigma ^{2}} is the variance. The standard deviation of the distribution is the positive value σ {\displaystyle \sigma } (sigma). A random
Normal_distribution
Method to determine the electronic structure of strongly correlated materials
≈ Σ i m p ( i ω n ) {\displaystyle \Sigma (k,i\omega _{n})\approx \Sigma _{imp}(i\omega _{n})} This approximation becomes exact in the limit of lattices
Dynamical_mean-field_theory
Matrix decomposition
the form M = U Σ V ∗ {\displaystyle \mathbf {M} =\mathbf {U} \mathbf {\Sigma } \mathbf {V} ^{*}} , where U {\displaystyle \mathbf {U} } is an
Singular_value_decomposition
Continuous mappings can be approximated by ones that are piecewise simple
In mathematics, the simplicial approximation theorem is a foundational result for algebraic topology, guaranteeing that continuous mappings can be (by
Simplicial approximation theorem
Simplicial_approximation_theorem
Oscillatory error in Fourier series
summation, such as Fejér summation or Riesz summation, or by using sigma-approximation. Using a continuous wavelet transform, the wavelet Gibbs phenomenon
Gibbs_phenomenon
Halo mass function
In physical cosmology, the Sheth–Tormen approximation is a halo mass function. It is named after Ravi K. Sheth and Giuseppe Tormen, who proposed their
Sheth–Tormen_approximation
Probability distribution
G(x;\sigma )} is the centered Gaussian profile: G ( x ; σ ) ≡ e − x 2 2 σ 2 2 π σ , {\displaystyle G(x;\sigma )\equiv {\frac {e^{-{\frac {x^{2}}{2\sigma ^{2}}}}}{{\sqrt
Voigt_profile
Fundamental theorem in probability theory and statistics
μ {\displaystyle \mu } and finite positive variance σ 2 {\displaystyle \sigma ^{2}} , and let X ¯ n {\displaystyle {\bar {X}}_{n}} denote the sample mean
Central_limit_theorem
Method in cosmology and astrophysics
Zeldovich approximation is a method in cosmology and astrophysics for describing the nonlinear evolution of the large-scale structure of the universe
Zeldovich_approximation
geometric settings. The input is a range space Σ = ( X , R ) {\displaystyle \Sigma =(X,{\mathcal {R}})} where X {\displaystyle X} is a universe of points in
Geometric_set_cover_problem
Analytical expression in statistics
Laplace's approximation or the quadratic approximation (QUAP) provides an analytical expression for a posterior probability distribution by fitting a Gaussian
Laplace's_approximation
Sigmoid shape special function
the desired interval of approximation. Another approximation is given by Sergei Winitzki using his "global Padé approximations": erf ( x ) ≈ sgn x
Error_function
Measure of a substance's ability to resist or conduct electric current
sigma _{xx}&\sigma _{xy}&\sigma _{xz}\\\sigma _{yx}&\sigma _{yy}&\sigma _{yz}\\\sigma _{zx}&\sigma _{zy}&\sigma
Electrical resistivity and conductivity
Electrical_resistivity_and_conductivity
Shorthand used in statistics
-1\sigma \leq X\leq \mu +1\sigma )&\approx 68.27\%\\\Pr(\mu -2\sigma \leq X\leq \mu +2\sigma )&\approx 95.45\%\\\Pr(\mu -3\sigma \leq X\leq \mu +3\sigma
68–95–99.7_rule
Mathematical model of financial markets
_{1}&={-\left(r-q-{1 \over {2}}\sigma ^{2}\right)+{\sqrt {\left(r-q-{1 \over {2}}\sigma ^{2}\right)^{2}+2\sigma ^{2}r}} \over {\sigma ^{2}}}\\\lambda _{2}&={-\left(r-q-{1
Black–Scholes_model
Effect of variables' uncertainties on the uncertainty of a function based on them
_{1}^{2}&\sigma _{12}&\sigma _{13}&\cdots \\\sigma _{21}&\sigma _{2}^{2}&\sigma _{23}&\cdots \\\sigma _{31}&\sigma _{32}&\sigma _{3}^{2}&\cdots
Propagation_of_uncertainty
Hungarian-American mathematician (1893–1974)
Claude Duchon, who named it after Lanczos due to Duchon's use of the sigma approximation in constructing the filter, a technique created by Lanczos. During
Cornelius_Lanczos
Physical law on the emissive power of black body
∘ = σ T 4 . {\displaystyle M^{\circ }=\sigma \,T^{4}.} The constant of proportionality, σ {\displaystyle \sigma } , is called the Stefan–Boltzmann constant
Stefan–Boltzmann_law
Scattering theory
} In the Born approximation for centrally symmetric field, the scattering amplitude and thus the cross section σ {\displaystyle \sigma } depends on the
Born_approximation
response filters using the FFT: Overlap–add method Overlap–save method Sigma approximation Dirichlet kernel — convolving any function with the Dirichlet kernel
List of numerical analysis topics
List_of_numerical_analysis_topics
In computer science, k-approximation of k-hitting set is an approximation algorithm for weighted hitting set. The input is a collection S of subsets of
K-approximation of k-hitting set
K-approximation_of_k-hitting_set
In statistics and machine learning, Gaussian process approximation is a computational method that accelerates inference tasks in the context of a Gaussian
Gaussian process approximations
Gaussian_process_approximations
Family of iterative methods
Stochastic approximation methods are a family of iterative methods typically used for root-finding problems or for optimization problems. The recursive
Stochastic_approximation
Method of approximating the properties of a composite material
In materials science, effective medium approximations (EMA) or effective medium theory (EMT) pertain to analytical or theoretical modeling that describes
Effective medium approximations
Effective_medium_approximations
Type of analog-to-digital converter
A successive-approximation ADC (or SAR ADC) is a type of analog-to-digital converter (ADC) that digitizes each sample from a continuous analog waveform
Successive-approximation_ADC
Theorem in probability theory
maximal error of approximation between the normal distribution and the true distribution of the scaled sample mean. The approximation is measured by the
Berry–Esseen_theorem
Theorem
In mathematics, the equioscillation theorem concerns the approximation of continuous functions using polynomials when the merit function is the maximum
Equioscillation_theorem
Probability distribution
_{j}e^{\mu _{j}}\right]+{\frac {\sigma ^{2}}{2}}-{\frac {\sigma _{Z}^{2}}{2}}.\end{aligned}}} For a more accurate approximation, one can use the Monte Carlo
Log-normal_distribution
Addition of several numbers or other values
also ways to generalize the use of many sigma notations. For example, one writes double summation as two sigma notations with different dummy variables
Summation
of probability, a heavy traffic approximation (sometimes called heavy traffic limit theorem or diffusion approximation) involves the matching of a queueing
Heavy_traffic_approximation
Smooth approximation of one-hot arg max
standard (unit) softmax function σ : R K → ( 0 , 1 ) K {\displaystyle \sigma :\mathbb {R} ^{K}\to (0,1)^{K}} , where K > 1 {\displaystyle K>1} , takes
Softmax_function
Method of data analysis
= U Σ V T {\displaystyle P=U\,\Sigma \,V^{T}} be its singular value decomposition. Then the best rank‑k approximation to P in the least‑squares (Frobenius‑norm)
Principal_component_analysis
Spectral linewidth of a laser beam
theoretically the linewidth of their device by making the reasonable approximations that their ammonia maser is a true continuous-wave (CW) maser, is a
Laser_linewidth
_{\lambda }^{B}(1)\mathbf {\chi } _{\sigma }^{D}(2)d\tau _{1}\,d\tau _{2}\ } The zero differential overlap approximation ignores integrals that contain the
Zero_differential_overlap
Method in statistics
\sigma ^{2}[g'(\theta )]^{2})}.} This concludes the proof. Alternatively, one can add one more step at the end, to obtain the order of approximation:
Delta_method
Mathematical analysis technique
{\begin{pmatrix}{\sigma _{1}^{2}}&{\sigma _{12}}&{\sigma _{13}}&\cdots &{\sigma _{1p}}\\{\sigma _{21}}&{\sigma _{2}^{2}}&{\sigma _{23}}&\cdots &{\sigma _{2p}}\\{\sigma
Experimental uncertainty analysis
Experimental_uncertainty_analysis
Shortest distance between two points on the surface of a sphere
short-distance approximation ( | Δ σ c | {\displaystyle |\Delta \sigma _{\text{c}}|} much smaller than 1 {\displaystyle 1} , cf. Small-angle approximation), Δ σ
Great-circle_distance
σ 2 {\displaystyle \sigma ^{2}} with denominator n {\displaystyle n} instead of n − 1 {\displaystyle n-1} . McKay's approximation, K {\displaystyle K}
McKay's approximation for the coefficient of variation
McKay's_approximation_for_the_coefficient_of_variation
Technique for the generative modeling of a continuous probability distribution
{\displaystyle \sigma _{t}:={\sqrt {1-{\bar {\alpha }}_{t}}}} σ ~ t := σ t − 1 σ t β t {\displaystyle {\tilde {\sigma }}_{t}:={\frac {\sigma _{t-1}}{\sigma _{t}}}{\sqrt
Diffusion_model
Probability distribution
( α D ) , i ≠ j {\displaystyle \Sigma _{ij}^{*}=\psi '\left(\alpha _{D}\right)\quad ,\quad i\neq j} This approximation is particularly accurate for large
Logit-normal_distribution
Business management method
Design for Six Sigma (DFSS) is a collection of best-practices for the development of new products and processes. It is sometimes deployed as an engineering
Design_for_Six_Sigma
Vecchia approximation is a Gaussian processes approximation technique originally developed by Aldo Vecchia, a statistician at United States Geological
Vecchia_approximation
Concept in probability theory
alternative to this approximation is the application of Monte Carlo simulations. Given μ X {\displaystyle \mu _{X}} and σ X 2 {\displaystyle \sigma _{X}^{2}}
Taylor expansions for the moments of functions of random variables
Taylor_expansions_for_the_moments_of_functions_of_random_variables
Degradation of AI models trained on synthetic data
trained model. Model collapse occurs for three main reasons: functional approximation errors sampling errors learning errors Importantly, it happens in even
Model_collapse
Model of a quantum/optical system
}a\right)\right)+2\gamma \left(\sigma \rho \sigma ^{\dagger }-{\frac {1}{2}}\left(\sigma ^{\dagger }\sigma \rho +\rho \sigma ^{\dagger }\sigma \right)\right)} The
Maxwell–Bloch_equations
Light scattering by small particles
the light is typically treated by the Mie theory, the discrete dipole approximation and other computational techniques. Rayleigh scattering applies to particles
Rayleigh_scattering
Fourier series Regressive discrete Fourier series Gibbs phenomenon Sigma approximation Dini test Poisson summation formula Spectrum continuation analysis
List of Fourier analysis topics
List_of_Fourier_analysis_topics
First-order method for approximating parallel transport of a vector along a curve
{\displaystyle A_{0}X_{0}} and A 1 X 1 {\displaystyle A_{1}X_{1}} as an approximation of the Levi-Civita parallelogramoid; the new segment A 1 X 1 {\displaystyle
Schild's_ladder
Bet sizing formula for long-term growth
-{\frac {(f\sigma )^{2}}{2}}\right)+f\sigma W_{1}\right)-1\right]\right)}+(1-f)r} For small μ {\displaystyle \mu } , σ {\displaystyle \sigma } , and W t
Kelly_criterion
Method in Itô calculus
solve this SDE on some interval of time [0, T]. Then the Euler–Maruyama approximation to the true solution X is the Markov chain Y defined as follows: Partition
Euler–Maruyama_method
Model of electronic band structures of solids
i,j\rangle ,\sigma }(c_{i,\sigma }^{\dagger }c_{j,\sigma }^{}+h.c.)} , c i σ † , c j σ {\displaystyle c_{i\sigma }^{\dagger },c_{j\sigma }} - creation
Tight_binding
Combinatorial optimization problem
issue by trying all values of k. A simple greedy approximation algorithm that achieves an approximation factor of 2 builds C {\displaystyle {\mathcal {C}}}
Metric_k-center
Statistical property
mean, σ x ¯ {\displaystyle {\sigma }_{\bar {x}}} , given by: σ x ¯ = σ n . {\displaystyle {\sigma }_{\bar {x}}={\frac {\sigma }{\sqrt {n}}}.} Practically
Standard_error
Technique in natural language processing
Sigma V^{T})(U\Sigma V^{T})^{T}=(U\Sigma V^{T})(V^{T^{T}}\Sigma ^{T}U^{T})=U\Sigma V^{T}V\Sigma ^{T}U^{T}=U\Sigma \Sigma ^{T}U^{T}\\X^{T}X&=&(U\Sigma
Latent_semantic_analysis
Energy transfer in the form of electromagnetic radiation
radiative transfer. The Eddington approximation is distinct from the two-stream approximation. The two-stream approximation assumes that the intensity is
Radiative_transfer
Probability distribution
for N much larger than n, the binomial distribution remains a good approximation, and is widely used. If the random variable X follows the binomial distribution
Binomial_distribution
Statistics function
\mu } and variance σ 2 {\displaystyle \sigma ^{2}} , then X = Y − μ σ {\displaystyle X={\frac {Y-\mu }{\sigma }}} is standard normal and P ( Y > y ) =
Q-function
Linear perturbations to solutions of nonlinear Einstein field equations
}={\frac {1}{2}}(\partial _{\sigma }\partial _{\mu }h_{\nu }^{\sigma }+\partial _{\sigma }\partial _{\nu }h_{\mu }^{\sigma }-\partial _{\mu }\partial _{\nu
Linearized_gravity
spaces that can be triangulated; this is formalized by the simplicial approximation theorem. A simplicial isomorphism is a bijective simplicial map such
Simplicial_map
Measure of a graph's centrality, based on shortest paths
{\displaystyle g(v)=\sum _{s\neq v\neq t}{\frac {\sigma _{st}(v)}{\sigma _{st}}}} where σ s t {\displaystyle \sigma _{st}} is the total number of shortest paths
Betweenness_centrality
Asymptotic analysis used when integrating rapidly-varying complex exponentials
In mathematics, the stationary phase approximation is a basic principle of asymptotic analysis, applying to functions given by integration against a rapidly-varying
Stationary phase approximation
Stationary_phase_approximation
Atom of helium
done by Albrecht Unsöld in 1927. Egil Hylleraas obtained an accurate approximation in 1929. Its success was considered to be one of the earliest signs
Helium_atom
Method for dividing a simplicial complex
the simplices and homotopic to the original maps (see also simplicial approximation). In general, such an assignment requires a refinement of the given
Barycentric_subdivision
Physical quantity that expresses internal forces in a continuous material
{\displaystyle {\begin{bmatrix}\sigma _{11}&\sigma _{12}&\sigma _{13}\\\sigma _{21}&\sigma _{22}&\sigma _{23}\\\sigma _{31}&\sigma _{32}&\sigma _{33}\end{bmatrix}}}
Stress_(mechanics)
In finance, Black's approximation is an approximate method for computing the value of an American call option on a stock paying a single dividend. It
Black's_approximation
Averages of repeated trials converge to the expected value
numerical results. The larger the number of repetitions, the better the approximation tends to be. The reason that this method is important is mainly that
Law_of_large_numbers
Matrix approximation problem in linear algebra
The orthogonal Procrustes problem is a matrix approximation problem in linear algebra. In its classical form, one is given two matrices A {\displaystyle
Orthogonal_Procrustes_problem
Method to approximate a probability distribution
propagation (EP) is a technique in Bayesian machine learning. EP finds approximations to a probability distribution. It uses an iterative approach that uses
Expectation_propagation
Equation
F_{p}^{x}=\left(\sigma _{xx}+{\frac {\partial \sigma _{xx}}{\partial x}}dx\right)dy\,dz-\sigma _{xx}dy\,dz+\left(\sigma _{yx}+{\frac {\partial \sigma _{yx}}{\partial
Cauchy_momentum_equation
Physical model defined on a lattice
{\displaystyle \langle \sigma \rangle } fill out the convex hull of S {\displaystyle S} . By making a suitable approximation, the energy functional becomes
Lattice_model_(physics)
Mathematical approximation of a function
called the nth Taylor polynomial of the function. Taylor polynomials are approximations of a function, which become generally more accurate as n increases.
Taylor_series
Model in quantum optics
optical cavity (or a bosonic field). The model assumes the rotating-wave approximation, neglects dissipation initially, and treats only a single field mode
Jaynes–Cummings_model
Probability distribution used in multivariate hypothesis testing
p ( Σ , n ) {\displaystyle \mathbf {A} \sim W_{p}(\Sigma ,m)\qquad \mathbf {B} \sim W_{p}(\Sigma ,n)} independent and with m ≥ p {\displaystyle m\geq
Wilks's_lambda_distribution
Rule for choosing histogram bins
x_{i}} let f ^ ( x ) {\displaystyle {\hat {f}}(x)} be the histogram approximation of some function f ( x ) {\displaystyle f(x)} . The integrated mean
Scott's_rule
Statistical confidence interval for success counts
with the normal approximation to the binomial: z α ≈ p − p ^ σ n {\displaystyle z_{\alpha }\ \approx \ {\frac {p-{\hat {p}}}{\sigma _{n}}}} where
Binomial proportion confidence interval
Binomial_proportion_confidence_interval
+ {\displaystyle X^{+}} and Σ − n Σ ′ ( R n ∖ X ) {\displaystyle \Sigma ^{-n}\Sigma '(\mathbb {R} ^{n}\setminus X)} are dual objects in the category of
Spanier–Whitehead_duality
Approximation method in statistics
}}_{j})=\sigma ^{2}\left(\left[X^{\mathsf {T}}X\right]^{-1}\right)_{jj}\approx {\hat {\sigma }}^{2}C_{jj},} σ ^ 2 ≈ S n − m {\displaystyle {\hat {\sigma }}^{2}\approx
Least_squares
Optimization algorithm
recurrence formula much like the one for Newton's method, except using approximations of the derivatives of the functions in place of exact derivatives. Newton's
Quasi-Newton_method
{\displaystyle x\mapsto \sigma ^{T}(t,x)\nabla u(t,x)} at t = t n {\displaystyle t=t_{n}} . Stack all sub-networks in the approximation step to form a deep
Deep backward stochastic differential equation method
Deep_backward_stochastic_differential_equation_method
Natural number
{\frac {99}{70}}=1.4142{\color {red}8571}\ldots } is a commonly used approximation of the irrational number √2 ".99" is frequently used as a price ender
99_(number)
Statistical rule of thumb
rule comes from the binomial distribution which is used as a discrete approximation to the normal distribution. If the function to be approximated f {\displaystyle
Sturges's_rule
equation in moments and use the Eddington approximation to radiative transfer (i.e. the diffusion approximation). In 3D the results are two equations for
Photon_diffusion
Filter in electronics and signal processing
filter is a filter whose impulse response is a Gaussian function (or an approximation to it, since a true Gaussian response would have infinite impulse response)
Gaussian_filter
Bayesian statistical inference method
this difference in perspective, empirical Bayes may be viewed as an approximation to a fully Bayesian treatment of a hierarchical model wherein the parameters
Empirical_Bayes_method
Effective theory of gravity
inspiraling compact objects like black holes. In the post-Newtonian approximation for a two body gravitational system, like a pair of inspiralling black
Non-relativistic general relativity
Non-relativistic_general_relativity
Optimization algorithm
differentiable or subdifferentiable). It can be regarded as a stochastic approximation of gradient descent optimization, since it replaces the actual gradient
Stochastic_gradient_descent
Measure of covariance of components of a random vector
_{1})(X_{2}-\mu _{2})]}{\sigma (X_{1})\sigma (X_{2})}}&\cdots &{\frac {\operatorname {E} [(X_{1}-\mu _{1})(X_{n}-\mu _{n})]}{\sigma (X_{1})\sigma (X_{n})}}\\\\{\frac
Covariance_matrix
from the study of universal approximation properties of two-layer neural networks. It has applications in approximation theory and statistical learning
Barron_space
Probability distribution
) . {\displaystyle \gamma _{2}={\frac {2}{\ \sigma ^{2}\ }}\left(1-\mu \ \sigma \ \gamma _{1}-\sigma ^{2}\right)~.} The entropy is given by: S = ln
Chi_distribution
Estimation method
transformed mean and covariance can only be approximated. The earliest approximation was to linearize the nonlinear function and apply the resulting Jacobian
Unscented_transform
Study of still or slow electric charges
electrostatics. This is called the "electrostatic approximation". The validity of the electrostatic approximation rests on the assumption that the electric field
Electrostatics
SIGMA APPROXIMATION
SIGMA APPROXIMATION
Female
Hindi/Indian
(सीमा) Variant spelling of Hindi Sima, SEEMA means "boundary, limit." Compare with another form of Seema.
Girl/Female
Tamil
Boundary, Border
Surname or Lastname
English
English : patronymic from a short form of the personal name Simon.Jewish (from Ukraine; Symes, Symis) : metronymic from the Yiddish female personal name Sime (see Sima).Benjamin Syms was a planter and philanthropist, probably the earliest inhabitant of any North American colony to bequeath property for the establishment of a free school. His name was spelled variously as Sims, Simes, Sym, Symms, Syms, and Symes. He was probably born in England, but was reported in the VA census of 1624/25 as age 33 and living at Basse’s Choice in what was later known as Isle of Wight County.
Girl/Female
Latin
Sign.
Surname or Lastname
English
English : patronymic from Sim.Jewish (Ashkenazic) : metronymic from the Yiddish female personal name Sime (see Sima).
Girl/Female
British, Danish, English, German, Swedish
Powerful Silence; Peaceful Victory
Female
Hindi/Indian
(सीमा) Hindi name SIMA means "boundary, limit." Compare with another form of Sima.
Male
Hebrew
(ש×Öµ×) Hebrew name SHEM means "conspicuous position, name, renown, sigma." In the bible, this is the name of a son of Noah.
Girl/Female
Scottish
Listener.
Girl/Female
Afghan, Arabic, Armenian, Australian, Farsi, French, Gujarati, Hebrew, Hindu, Indian, Malayalam, Muslim, Sanskrit, Tamil
Limit; Border; Listener; Precious Thing; Treasure; Boundary; Bank; Shore
Girl/Female
Arabic, Muslim
Peace
Girl/Female
Hindu
Boundary, Border
Girl/Female
Danish, German, Latin, Scandinavian, Swedish
Sign; Signal; Victory
Boy/Male
Arabic, Muslim
Gold Stigma of a Flower; Derived from Zarparan
Boy/Male
Norse
Victorious defender.
Boy/Male
Hindu, Indian, Muslim
Powerful; Mighty; Strong; Rich; Successful
Surname or Lastname
English (Midlands)
English (Midlands) : from the Middle English personal name, a pet form of Sim.Jewish (from Belarus) : metronymic from Simke, a pet form of the Yiddish female personal name Sime (see Sima) with the eastern Slavic possessive suffix -in.
SIGMA APPROXIMATION
SIGMA APPROXIMATION
Boy/Male
Muslim
The praised one
Boy/Male
Gujarati, Hindu, Indian, Kannada, Marathi, Sanskrit, Tamil, Telugu
Strong; Miracle; First Ray of Sun
Boy/Male
Muslim
Sun of the faith
Girl/Female
Muslim/Islamic
Praising Allah
Girl/Female
Hindu, Indian
River Name
Surname or Lastname
Americanized spelling of German Deis.English
Americanized spelling of German Deis.English : probably a variant of Dice or Dye.
Boy/Male
Hindu
Classic, Most excellent, Best
Girl/Female
Tamil
Kimatra | கிமாதà¯à®°à®¾
Seduce
Boy/Male
Anglo Saxon
Fierce.
Girl/Female
Muslim
Caesar
SIGMA APPROXIMATION
SIGMA APPROXIMATION
SIGMA APPROXIMATION
SIGMA APPROXIMATION
SIGMA APPROXIMATION
v. t.
To apply pollen to (a stigma).
v. t.
One of the apertures of the gill of an ascidian, and of Amphioxus.
pl.
of Stigma
v. t.
A mark made with a burning iron; a brand.
v. t.
That part of a pistil which has no epidermis, and is fitted to receive the pollen. It is usually the terminal portion, and is commonly somewhat glutinous or viscid. See Illust. of Stamen and of Flower.
pl.
of Stigma
v. t.
One of the external openings of the tracheae of insects, myriapods, and other arthropods; a spiracle.
v. t.
A small spot, mark, scar, or a minute hole; -- applied especially to a spot on the outer surface of a Graafian follicle, and to spots of intercellular substance in scaly epithelium, or to minute holes in such spots.
n. pl.
The signs, abbreviations, letters, or characters standing for words, shorthand, etc., in ancient manuscripts, or on coins, medals, etc.
v. t.
One of the apertures of the pulmonary sacs of arachnids. See Illust. of Scorpion.
v. t.
A point so connected by any law whatever with another point, called an index, that as the index moves in any manner in a plane the first point or stigma moves in a determinate way in the same plane.
v. t.
A red speck upon the skin, produced either by the extravasation of blood, as in the bloody sweat characteristic of certain varieties of religious ecstasy, or by capillary congestion, as in the case of drunkards.
a.
Of or pertaining to a stigma or stigmata.
pl.
of Sigma
v. t.
Marks believed to have been supernaturally impressed upon the bodies of certain persons in imitation of the wounds on the crucified body of Christ. See def. 5, above.
n.
Stigma; brand; reproach.
v. t.
Any mark of infamy or disgrace; sign of moral blemish; stain or reproach caused by dishonorable conduct; reproachful characterization.
n.
A stigma. See Stigma, n., 6 (a) & (b).
n.
The Greek letter /, /, or / (English S, or s). It originally had the form of the English C.
n.
pl. of Stigma.