1. A computer-implemented method of computing a steady state of a voltage controlled oscillator, the method comprising the steps of:
generating a set of one or more differential algebraic equations representative of the of an electronic circuit, for analysis of the voltage controlled oscillator, the set of one or more differential algebraic equations including a known period or a known frequency of oscillation of the voltage controlled oscillator and an unknown control voltage of the voltage controlled oscillator that generates the period or the frequency of oscillation;
modifying the set of one or more differential algebraic equations to obtain a set of one or more matrix equations corresponding to the differential algebraic equations; and
obtaining a solution to the set of one or more matrix equations using a Krylov subspace method, the solution including the control voltage of the voltage controlled oscillator in steady state,
wherein the set of one or more differential algebraic equations is in the form of:
\u2146
q
\u2061
(
x
)
\u2146
t
+
f
\u2061
(
x
)
+
b
+
ce
=
0
,
where x represents a steady state solution, t represents time, q(x) and f(x) represent parameters of the voltage controlled oscillator that are functions of the steady state solution, b represents an independent source of the voltage controlled oscillator except a control source, and ce represents the control source of the voltage controlled oscillator wherein c is a control voltage scalar and e is a vector with one or two nonzero entries that are either 1 or \u22121.
2. The computer-implemented method of claim 1, wherein the set of one or more differential algebraic equations is modified using a finite difference method in time domain to obtain the set of one or more matrix equations.
3. The computer-implemented method of claim 1, wherein the set of one or more differential algebraic equations is modified using a shooting method in time domain to obtain the set of one or more matrix equations.
4. The computer-implemented method of claim 1, wherein the set of one or more differential algebraic equations is modified using a harmonic balance method in frequency domain to obtain the set of one or more matrix equations.
5. The computer-implemented method of claim 1, wherein the step of modifying the set of one or more differential algebraic equations comprises obtaining a Jacobian matrix corresponding to the set of one or more matrix equations, the set of one or more matrix equations being solved using the Krylov subspace method with a preconditioner for the Krylov subspace method being derived at least in part from the Jacobian matrix.
6. A computer system configured to compute the steady state of a voltage controlled oscillator, the computer system comprising:
a model equations storage module storing a plurality of differential algebraic equations corresponding to a plurality of circuit components of the voltage controlled oscillator; and
a circuit simulation engine coupled to the model equations storage module configured to:
generate a set of one or more differential algebraic equations representative of the of an electronic circuit, for analysis of the voltage controlled oscillator, the set of one or more differential algebraic equations including a known period or a known frequency of oscillation of the voltage controlled oscillator and an unknown control voltage of the voltage controlled oscillator that generates the period or the frequency of oscillation;
modify the set of one or more differential algebraic equations to obtain a set of one or more matrix equations corresponding to the differential algebraic equations; and
obtain a solution to the set of one or more matrix equations using a Krylov subspace method, the solution including the control voltage of the voltage controlled oscillator in steady state
wherein the set of one or more differential algebraic equations is in the form of:
\u2146
q
\u2061
(
x
)
\u2146
t
+
f
\u2061
(
x
)
+
b
+
ce
=
0
,
where x represents a steady state solution, t represents time, q(x) and f(x) represent parameters of the voltage controlled oscillator that are functions of the steady state solution, b represents an independent source of the voltage controlled oscillator except a control source, and ce represents the control source of the voltage controlled oscillator wherein c is a control voltage scalar and e is a vector with one or two nonzero entries that are either 1 or \u22121.
7. The computer system of claim 6, wherein the circuit simulation engine modifies the set of one or more differential algebraic equations using a finite difference method in time domain to obtain the set of one or more matrix equations.
8. The computer system of claim 6, wherein the circuit simulation engine modifies the set of one or more differential algebraic equations using a shooting method in time domain to obtain the set of one or more matrix equations.
9. The computer system of claim 6, wherein the circuit simulation engine modifies the set of one or more differential algebraic equations using a harmonic balance method in frequency domain to obtain the set of one or more matrix equations.
10. The computer system of claim 6, wherein the circuit simulation engine obtains a Jacobian matrix corresponding to the set of one or more matrix equations, the set of one or more matrix equations being solved using the Krylov subspace method with a preconditioner for the Krylov subspace method being derived at least in part from the Jacobian matrix.
11. A computer readable medium storing a computer program product configured to perform a computer-implemented method of computing the steady state of a voltage controlled oscillator, the method comprising the steps of:
generating a set of one or more differential algebraic equations representative of the of an electronic circuit, for analysis of the voltage controlled oscillator, the set of one or more differential algebraic equations including a known period or a known frequency of oscillation of the voltage controlled oscillator and an unknown control voltage of the voltage controlled oscillator that generates the period or the frequency of oscillation;
modifying the set of one or more differential algebraic equations to obtain a set of one or more matrix equations corresponding to the differential algebraic equations; and
obtaining a solution to the set of one or more matrix equations using a Krylov subspace method, the solution including the control voltage of the voltage controlled oscillator in steady state,
wherein the set of one or more differential algebraic equations is in the form of:
\u2146
q
\u2061
(
x
)
\u2146
t
+
f
\u2061
(
x
)
+
b
+
ce
=
0
,
where x represents a steady state solution, t represents time, q(x) and f(x) represent parameters of the voltage controlled oscillator that are functions of the steady state solution, b represents an independent source of the voltage controlled oscillator except a control source, and ce represents the control source of the voltage controlled oscillator wherein c is a control voltage scalar and e is a vector with one or two nonzero entries that are either 1 or \u22121.
12. The computer readable medium of claim 11, wherein the set of one or more differential algebraic equations is modified using a finite difference method in time domain to obtain the set of one or more matrix equations.
13. The computer readable medium of claim 11, wherein the set of one or more differential algebraic equations is modified using a shooting method in time domain to obtain the set of one or more matrix equations.
14. The computer readable medium of claim 11, wherein the set of one or more differential algebraic equations is modified using a harmonic balance method in frequency domain to obtain the set of one or more matrix equations.
15. The computer readable medium of claim 11, wherein the step of modifying the set of one or more differential algebraic equations further comprises obtaining a Jacobian matrix corresponding to the set of one or more matrix equations, the set of one or more matrix equations being solved using the Krylov subspace method with a preconditioner for the Krylov subspace method being derived at least in part from the Jacobian matrix.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A system for electronically evaluating criticality of a weakness in a business process, the system comprising:
an input module configured to receive business process system data and business process scoring data, wherein the business process scoring data comprises a resiliency score quantifying a level of mitigation available for a failure mode;
a processor configured to assess the criticality of a weakness in the business process, the criticality dependent on the business process system data and the business process scoring data; and
an output module configured to output a score quantifying the criticality of the weakness,
wherein the criticality of the weakness in the business process is a modified Risk Profile Number (mRPN) defined by the equation
mRPN=OR*OBI*10\u2212(0.9)D*10\u2212(0.9)R,
wherein:
OR comprises an occurrence rate for a failure;
OBI comprises an overall business impact;
D comprises a probability of detecting a failure; and
R comprises the resiliency score quantifying the level of mitigation available for the failure mode.
2. The system of claim 1 wherein the business process system data comprises data related to a business function of the business process.
3. The system of claim 1 wherein the business process system data further comprises data related to a functional process step carried out in the course of the business process.
4. The system of claim 3 wherein the business process scoring data comprises data related to a failure of a functional process step.
5. A non-transitory computer readable storage medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method for evaluating criticality of a weakness in a business process, said method comprising:
receiving business process system data, and storing the business process system data in machine readable memory;
receiving business process scoring data, and storing the business process scoring data in machine readable memory, wherein the business process scoring data comprises a resiliency score quantifying a level of mitigation available for a failure mode;
using a processor module, calculating a score quantifying the criticality of a weakness in the business process, the score dependent on the business process system data and the business process scoring data,
wherein the criticality of the weakness in the business process is a modified Risk Profile Number (mRPN) defined by the equation
mRPN=OR*OBI*10\u2212(0.9)D*10\u2212(0.9)R,
wherein:
OR comprises an occurrence rate for a failure;
OBI comprises an overall business impact;
D comprises a probability of detecting a failure; and
R comprises the resiliency score quantifying the level of mitigation available for the failure mode.
6. The media of claim 5 wherein, in the method, the business process system data comprises:
a business function associated with the business process; and
a measure of transaction volume associated with the business function.
7. The media of claim 5 wherein, in the method, the business process system data further comprises:
a functional process step carried out in the course of the business process; and
the failure mode of the functional process step.
8. The media of claim 7 wherein, in the method, the functional process step is defined as the integration between a source component and a destination component.
9. The media of claim 7 wherein, in the method, the business process scoring data comprises a failure occurrence rate score quantifying the probability of occurrence for the failure mode.
10. The media of claim 7 wherein, in the method, the business process scoring data comprises a failure detection score quantifying a probability of detecting the failure mode.
11. The media of claim 5 wherein, in the method, the processor module is further configured to calculate a weight for each business function, the weight dependent on the transaction volume and a criticality score.
12. The media of claim 5 wherein the processor is further configured to calculate a risk profile number, quantifying the criticality of the weakness and the possibility of mitigation.
13. A method for electronically evaluating criticality of a weakness in a business process, the method comprising:
receiving business process system data, and storing the business process system data in machine readable memory;
receiving business process scoring data, and storing the business process scoring data in machine readable memory, wherein the business process scoring data comprises a resiliency score quantifying a level of mitigation available for a failure mode; and
using a processor, calculating a score quantifying the criticality of a weakness in the business process, the criticality dependent on the business process system data and the business process scoring data,
wherein the criticality of the weakness in the business process is a modified Risk Profile Number (mRPN) defined by the equation
mRPN=OR*OBI*10\u2212(0.9)D*10\u2212(0.9)R,
wherein:
OR comprises an occurrence rate for a failure;
OBI comprises an overall business impact;
D comprises a probability of detecting a failure; and
R comprises the resiliency score quantifying the level of mitigation available for the failure mode.
14. The method of claim 13 wherein the business process system data comprises:
a business function achieved through the business process;
a functional process step associated with carrying out the process; and
the failure mode of the functional process step.
15. The method of claim 14 wherein the business process scoring data comprises:
an assessment of the criticality of a business function to the success of the business process; and
an assessment of the criticality of a functional process step to the achievement of the business function.
16. The method of claim 13 wherein the business process scoring data comprises an assessment of the probability of detecting a failure mode.