# US 2024/0202066 A1 · Systems and methods for fault detection and mitigation using adaptive and real-time degeneracy > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2024/0202066 A1 - Document ID: US20240202066A1 - Status: Published application - Kind: A1 - Application number: 18/539,778 - Filed: 2023-12-14 - Published: 2024-06-20 - Earliest claimed: 2022-12-14 - Applicants: University of Cincinnati - Inventors: Corey L. Butts; Rashmi Jha; Temesgen Messay Kebede; David Anthony Kapp - Web page: https://patentgrep.com/patent/US20240202066A1 ## CPC - G06F 11/0793: {Remedial or corrective actions (recovery from an exception in an instruction pipeline G06F9/3861; by retry G06F11/1402; for recovering from a failure of a protocol instance or entity H04L69/40)} - G06F 11/079: {Root cause analysis, i.e. error or fault diagnosis (in a hardware test environment G06F11/22; in a software test environment G06F11/36)} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Systems and methods disclosed herein provide training an artificial neural network (ANN) on buffered input and output samples of an original component within a system such that the ANN is configured to produce a degenerate component, the degenerate component configured to generate the same outputs as the original component; comparing the outputs from the original component to outputs of the degenerate component during actual component operation; and in the event of a failure of the original component, replacing the original component with the degenerate component. ## Claims ### Claim 1 A detection and mitigation system comprising: an artificial neural network (ANN) that is configured to create a degenerate component that is functionally identical but structurally different from an original component in the system and produces the same output as the original component, wherein the ANN is configured to compare outputs of the degenerate component to outputs of the original component, and wherein the ANN is configured to replace the outputs of the original component with the outputs of the degenerate component when a difference between the outputs of the original component and the outputs of the degenerate component is detected. ### Claim 2 (depends on 1) The detection and mitigation system of claim 1, wherein the system comprises an embedded computer system. ### Claim 3 (depends on 1) The detection and mitigation system of claim 1, wherein the ANN is configured to alert the detection and mitigation system of a faulty, a failed, or a compromised original component. ### Claim 4 A method of detecting a component failure in a digital system comprising the steps of: training an artificial neural network (ANN) on buffered input and output samples of an original component within a system such that the ANN is configured to produce a degenerate component, the degenerate component configured to generate the same outputs as the original component; comparing the outputs from the original component to outputs of the degenerate component during actual component operation; and in the event of a failure of the original component, replacing the original component with the degenerate component. ### Claim 5 (depends on 4) The method of claim 4, wherein after the original component is replaced by the degenerate component, the ANN is configured to produce a new degenerate component, wherein the new degenerate component is configured to generate the same outputs as the original component. ### Claim 6 (depends on 5) The method of claim 5, wherein the ANN is configured to dynamically produce the degenerate component. ### Claim 7 (depends on 4) The method of claim 4, wherein the ANN is configured to produce a plurality of the degenerate components. ### Claim 8 (depends on 4) The method of claim 4, wherein the digital system includes a software defined radio system. ### Claim 9 (depends on 4) The method of claim 4, wherein the original component includes an integrated circuit comprising a field-programmable gate array or a system-on-a-chip. ### Claim 10 (depends on 9) The method of claim 9, where the original component fails due to a fault. ### Claim 11 (depends on 10) The method of claim 10, wherein the fault is selected from at least one of a single-event upset error, a hardware trojan, genuine design error, or any combination thereof. ### Claim 12 (depends on 4) The method of claim 4, wherein the buffered input and output samples of the original component are normalized to a predetermined range for model convergence. ### Claim 13 (depends on 4) The method of claim 4, further comprising comparing the outputs from the original component to outputs of the degenerate component using a mean squared error loss function. ### Claim 14 A non-transitory, computer-readable medium comprising instructions that, when executed by at least one processor, cause the at least one processor to perform one or more operations comprising: training an artificial neural network (ANN) on buffered input and output samples of an original component within a system such that the ANN is configured to produce a degenerate component, the degenerate component configured to generate the same outputs as the original component; comparing the outputs from the original component to outputs of the degenerate component during actual component operation; and in the event of a failure of the original component, replacing the original component with the degenerate component. ### Claim 15 (depends on 14) The non-transitory computer-readable medium of claim 14, wherein after the original component is replaced by the degenerate component, the ANN is configured to produce a new degenerate component, wherein the new degenerate component is configured to generate the same outputs as the original component. ### Claim 16 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the ANN is configured to dynamically produce the degenerate component. ### Claim 17 (depends on 14) The non-transitory computer-readable medium of claim 14, wherein the ANN is configured to produce a plurality of the degenerate components. ### Claim 18 (depends on 14) The non-transitory computer-readable medium of claim 14, wherein the digital system includes a software defined radio system. ### Claim 19 (depends on 14) The non-transitory computer-readable medium of claim 14, wherein the original component includes an integrated circuit comprising a field-programmable gate array or a system-on-a-chip. ### Claim 20 (depends on 19) The non-transitory computer-readable medium of claim 19, where the original component fails due to a fault.