Symbols
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Cosine | \(\cos\)
Pi | \(\pi\)
Sine | \(\sin\)
Angle | \(\theta\)
Circumference | \(c\)
Diameter | \(d\)
Value of f at x | \(f(x)\)
Imaginary Number | \(j\)
Real Part | \(\Re\)
Imaginary Part | \(\Im\)
Complex Conjugate | \(^{*}\)
Complex Number | \(Z\)
Legrange's Derivative Notation | \('\)
Legrange's Derivative Function | \(f'(x)\)
Integral | \(\int\)
Eulers Constant | \(e\)
Generic Function 1 (Calculus) | \(u\)
Generic Function 2 (Calculus) | \(v\)
Angle 2 | \(\phi\)
Set of integers | \(\mathbb{Z}\)
Generic Variable | \(x\)
Generic Variable 2 | \(y\)
Generic Variable 3 | \(z\)
Product | \(\prod\)
Iterator | \(i\)
Set of whole numbers | \(\mathbb{W}\)
Generic Constant 1 | \(a\)
Generic Constant 2 | \(b\)
Generic Constant 3 | \(c\)
Sampling Frequency | \(f_{s}\)
Sampling Period | \(T_{s}\)
Discrete function | \(x\)
Time | \(t\)
Signal Function | \(x\)
A Whole Number | \(n\)
An Integer | \(k\)
Normalized Radian Frequency | \(\hat \omega\)
Radian Frequency | \(\omega\)
Frequency | \(f\)
Sum | \(\sum\)
Normalized Frequency | \(\hat f\)
Kronecker Delta Function | \(\delta\)
Finite Impulse Response | \(h\)
Order of a Difference Equation | \(M\)
Impulse Response | \(h\)
Radius | \(r\)
Convolution | \(\ast\)
Response of Filter | \(y\)
Generic Function | \(f\)
Sinusoidal Response of a Finite Impulse Response Filter | \(H\)
Step Size | \(h\)
Limit | \(\lim\)
Gradient | \(m\)
Y-intercept | \(C\)
Differential | \(\:d\)
Number of Subintervals | \(n\)
Infinity | \(\infty\)
Change in Variable | \(\Delta\)
Width of a Rectangle | \(W\)
Height of a Rectangle | \(H\)
Area | \(A\)
Constant of Integration | \(C\)
Generic Function 2 | \(g\)
Period | \(T\)
Fundamental Period | \(T_{0}\)
A Second Integer | \(n\)
Z-Transform | \(X\)
Loss Function | \(L\)
Model | \(h\)
Input | \(u\)
Ground Truth | \(y\)
Set of Reals | \(\mathbb{R}\)
Activation Function | \(\sigma\)
Optimal Model | \(\hat{f}\)
Expectation | \(E\)
Random Variable Input | \(U\)
Random Variable Output | \(Y\)
Risk | \(R\)
Hypothesis Space | \(\mathcal{H}\)
Parameter Space | \(\Theta\)
Sample | \(S\)
Weight Vector | \(\theta\)
Regularization | \(\textup{reg}\)
Model's parameters | \(\theta\)
Gradient | \(\nabla\)
Learning Rate | \(\mu\)
RNN Hidden State | \(\mathbf{h}\)
Network (Function Approximator) | \(\mathcal{N}\)
Polynomial | \(p\)
Polynomial Constant | \(\omega\)
Neuron activation | \(x^\kappa_i\)
Layer size | \(L\)
Layer activation | \(x^\kappa\)
Weights matrix | \(\mathbf{W}\)
Output activation vector | \(\mathbf{y}\)
Sigmoid | \(\sigma\)
Bias | \(\mathcal{b}\)
Activation Vector | \(\mathcal{x}\)
Number of Inputs | \(K\)
Number of Neurons | \(L\)
Number of Outputs | \(M\)
Secondary Iterator | \(j\)
State of the input neuron of LSTM | \(u\)
State of the input gate neuron in LSTM | \(g^\text{input}\)
State of the output gate of an LSTM | \(g^\text{output}\)
State of the forget gate in an LSTM | \(g^\text{forget}\)
Memory cell of an LSTM | \(c\)
Generic Ordinary Differential Equation | \(z\)
Generic Function 3 | \(z\)
Update Operator | \(T\)
State Space of Dynamical System | \(\mathcal{X}\)
System State | \(\mathbf{x}\)
Output Function | \(O\)
System Output | \(\mathbf{y}\)
System Input | \(\mathbf{u}\)
Potential of a Unit | \(a\)
Markov Transition Matrix | \(T\)
Energy | \(E\)
Training pattern | \(\xi\)
Random Variable | \(X\)
Transpose | \(T\)
Error of a Neuron | \(\delta\)
Generic Neuron Activation | \(x\)
Identity Matrix | \(I\)
Number of Samples | \(N\)
Temperature | \(T\)
Partition Function (Normalization constant) | \(Z\)
Microstate | \(\mathbf{s}\)
Space of Possible Microstates | \(S\)
Proposed Next State | \(\mathbf{x}^*\)
Proposal Distribution | \(P_{\text{prop}}\)
Acceptance Probability (Acceptance Function) | \(P_{\text{accept}}\)
General Measure Function | \(F\)
Weight in BM | \(w\)
Logarithm | \(\log\)
Probability Distribution | \(P\)
Average Probability Overall | \(q_{ij}\)
Average Probability Samples | \(p_{ij}\)