Symbol Response Memory Validation for Reliable Pattern Analysis
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Solution Overview
Problem
Conventional computing systems face inefficiencies in pattern recognition due to the increasing volume of data and number of patterns to be identified, leading to bottlenecks in processing speed and accuracy, particularly in detecting spam or malware, and existing hardware struggles to validate configuration content in electronic devices used for data analysis.
Innovation Solution
A state machine engine with a hierarchical structure of finite state machine lattices that operate in parallel, allowing for rapid analysis of complex patterns and validation of configuration content by employing a cascaded circuit approach similar to the human brain's pattern recognition mechanisms, including an error detection engine to ensure accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional computing systems process pattern recognition tasks, then processing capability is provided, but processing speed and efficiency deteriorate due to increasing data volume and pattern complexity
Solution Approach 1:
The system divides pattern recognition into multiple hierarchical levels (lower layers for raw signal analysis, higher layers for complex pattern analysis). Each level processes specific aspects of the data independently, allowing parallel processing and improving overall speed without requiring a single complex system to handle all patterns simultaneously.
Solution Approach 2:
The patent introduces a hierarchical dimension to pattern recognition, organizing processing layers vertically rather than horizontally. This multi-layer architecture allows simultaneous processing of multiple pattern types at different abstraction levels, effectively increasing processing capacity without linearly increasing system complexity.
2Speed
If hardware distributes data stream among multiple parallel circuits for pattern searching, then processing speed improves, but intermediate results become larger than original input data causing system bottlenecks
Solution Approach 1:
The system extracts only the essential pattern matching results from each parallel circuit rather than transmitting all intermediate processing data. By taking out only the relevant match information and discarding redundant intermediate states, the system maintains high processing speed while keeping data volume manageable.
Solution Approach 2:
Instead of having parallel circuits process complete data streams and generate comprehensive intermediate results, the system inverts the approach by having each circuit focus on detecting specific pattern features and reporting only when matches are found. This reduces intermediate data volume while maintaining processing throughput.
3Adaptability or versatility
If configuration content is stored in electronic devices for data analysis, then pattern recognition capability is provided, but reliability deteriorates due to bit failure or corruption
Solution Approach 1:
The system performs preliminary validation of configuration content before using it for pattern recognition. By checking the integrity of stored pattern data and configuration parameters in advance, the system prevents corrupted data from affecting recognition accuracy, thereby maintaining reliability without reducing adaptability.
Solution Approach 2:
The system implements feedback mechanisms that monitor configuration content integrity during operation. When bit failures or corruption are detected, the system can request retransmission or correction of configuration data, ensuring reliable pattern recognition capability while maintaining the ability to recognize diverse patterns.
Data Source
AI summary
Configuration content of electronic devices used for data analysis may be altered due to bit failure or corruption, for example. Accordingly, in one embodiment, a device includes a plurality of blocks, each block of the plurality of blocks includes a plurality of rows, each row of the plurality of rows includes a plurality of configurable elements, each configurable element of the plurality of configurable elements includes a data analysis element including a memory component programmed with configuration data. The data analysis element is configured to analyze at least a portion of a data stream based on the configuration data and to output a result of the analysis. The device also includes an error detection engine (EDE) configured to perform integrity validation of the configuration data.