Symbol Response Memory Validation for Reliable Pattern Recognition
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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 effectively.
Innovation Solution
A state machine engine with a hierarchical structure of finite state machine lattices operates in parallel, analyzing data streams for multiple patterns simultaneously, utilizing a cascaded approach similar to the human brain's neural layers, and includes an error detection engine to validate configuration content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional computing systems process pattern recognition sequentially, then processing accuracy is maintained, but processing speed deteriorates due to increasing data volume and pattern complexity
Solution Approach 1:
The patent divides the pattern recognition task into multiple segments by distributing data streams among a plurality of circuits, where each circuit determines whether the data stream matches a specific portion of a pattern. This segmentation enables parallel processing of different pattern portions simultaneously, improving processing speed while maintaining accuracy through subsequent result aggregation.
Solution Approach 2:
The patent transitions from sequential one-dimensional processing to multi-dimensional parallel processing by organizing circuits in parallel architectures that can evaluate multiple patterns simultaneously. This dimensional expansion allows the system to process increasing volumes of data and patterns without proportionally increasing processing time.
2Adaptability or versatility
If a large number of circuits operate in parallel to search data streams, then pattern detection capability is improved, but intermediate results become larger than original input data causing system bottlenecks
Solution Approach 1:
The patent extracts only the essential matching information from parallel circuit operations, focusing on determining whether data streams match specific pattern portions rather than processing complete pattern data. This extraction approach reduces intermediate result volume while preserving the critical information needed for final pattern recognition decisions.
Solution Approach 2:
The patent implements partial action by having circuits evaluate only specific portions of patterns rather than complete patterns, allowing parallel processing with reduced data volume. The system performs sufficient evaluation to detect patterns without processing excessive intermediate data, balancing detection capability with data volume management.
3Adaptability or versatility
If configuration content is stored in electronic devices for data analysis, then pattern recognition functionality is enabled, but bit failure or corruption may alter configuration content reducing reliability
Solution Approach 1:
The patent implements preliminary validation of configuration content before it is used for pattern recognition operations. By validating configuration data in advance, the system ensures integrity and detects potential bit failures or corruption before they can compromise pattern recognition accuracy, maintaining reliability while preserving configuration flexibility.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor and validate configuration content, providing continuous verification of data integrity. This feedback loop enables the system to detect and respond to configuration corruption, maintaining reliable operation while allowing flexible configuration changes.
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.