Facilitating neural networks
US-2019065956-A1 · Feb 28, 2019 · US
US10360285B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10360285-B2 |
| Application number | US-201715802342-A |
| Country | US |
| Kind code | B2 |
| Filing date | Nov 2, 2017 |
| Priority date | Nov 2, 2017 |
| Publication date | Jul 23, 2019 |
| Grant date | Jul 23, 2019 |
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A method of computing includes defining a first atomic random variable (ARV) and first random variable (RV) in a programming language system. The first ARV having a non-deterministic value of either zero according to a second probability or one according to a first probability. A sum of the first probability and the second probability is one. A covariance of the first ARV and a second ARV is zero. The first RV has a first indefinite value at a first definite probability and includes a polynomial of one or more atomic random variables (ARVS) that includes the first ARV. The method includes executing a computer instruction that includes a mathematical operation involving the first RV as a basic data type and produces a second RV having a second indefinite value at a second definite probability, represents a result distribution, and tracks a response to the one or more ARVS.
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What is claimed is: 1. A method of quantum-inspired computing, the method comprising: defining a first atomic random variable (ARV) in a programming language system, the first ARV having a non-deterministic value of either zero or one, a first probability of having a value of one, and a second probability of having a value of zero; a sum of the first probability and the second probability is one; and a covariance of the first ARV and a second ARV is zero; defining a first random variable (RV) in the programming language system, the first RV having a first indefinite value at a first definite probability and includes a polynomial of one or more atomic random variables (ARVS) that includes the first ARV; and executing a computer instruction that includes a mathematical operation involving the first RV as a basic data type, the executing producing a second RV that has a second indefinite value at a second definite probability, represents a result distribution, and tracks a response to the one or more ARVS. 2. The method of claim 1 , wherein: a mean of the first ARV is equal to the first probability; a mean square of the first ARV is equal to the first probability; an n-th moment of the first ARV is equal to the first probability for all values of n; a variance of the first ARV is equal to a product of the first probability and the second probability; and an m-th power of the first ARV is equal to the first ARV for all values of m. 3. The method of claim 1 , wherein the first ARV is defined according to ARV expressions: X i ∈{0,1}; 0 ≤p i ≤1; Pr[ X i =1]= p i ; Pr[ X i =0]=1 −p i ; and Cov( X i ,X k )=0 for i≠k ; in which: i and k represent indexing variables; p i represents a first probability indexed according to the indexing variable i; X i represents an ARV indexed according to the indexing variable i; X k represents an ARV indexed according to the indexing variable k; Pr[ ] represents a probability function; and Cov( ) represents a covariance function. 4. The method of claim 3 , wherein entropy of the ARV is approximated according to an approximate entropy expression: S [ X i ]≃ log 2−2 q i 2 ; in which: S[X i ] represents the entropy, q i represents p i −½, and log 2 represents a natural log of 2 base Napier's constant (e). 5. The method of claim 3 , wherein: the first random variable is a quadratic random variable (QRV); and the QRV is defined according to the QRV expressions: Y A ≡ X → T A X → ; X → ≡ [ X 0 X 1 X 2 ⋯ X m ] T ; A ≡ [ a 0 , 0 a 0 , 1 a 0 , 2 … a 0 , m a 1 , 0 a 1 , 1 a 1 , 2 … a 1 , m a 2 , 0 a 2 , 1 a 2 ,
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