FIELD: computers.
SUBSTANCE: system has memory, capable of storage of correlithmic object data, representing a point in local space, and processor, capable of using a metric, which is a formula for calculation of values between correlithmic object and said space points. Other variant of processing system has memory, capable of storing data about multiple cells, and processor, capable during operation of taking input value for individual cell from each of given cells of multiple cells, and to form second output value, connected to individual cell, on basis of input values, determined on basis of imaging means data. Methods describe operation of said systems.
EFFECT: broader functional capabilities.
10 cl, 4 dwg, 23 tbl
| Title | Year | Author | Number |
|---|---|---|---|
| ARCHITECTURE FOR INTELLECTUAL COMPUTING AND INFORMATION-MEASURING SYSTEMS WITH FUZZY MEDIA COMPUTATIONS | 2018 |
|
RU2680201C1 |
| METHOD AND SYSTEM FOR CLASSIFYING DATA FOR IDENTIFYING CONFIDENTIAL INFORMATION | 2019 |
|
RU2759786C1 |
| METHOD AND SYSTEM FOR GENERATING SYNTHETIC DATA | 2023 |
|
RU2824524C1 |
| METHOD FOR DIAGNOSING A COMPLEX OF ON-BOARD EQUIPMENT OF AIRCRAFT BASED ON UNSUPERVISED MACHINE LEARNING WITH AUTOMATIC DETERMINATION OF MODEL TRAINING PARAMETERS | 2023 |
|
RU2818858C1 |
| METHOD FOR DETECTING ANOMALIES IN MULTIDIMENSIONAL DATA | 2021 |
|
RU2773010C1 |
| METHOD FOR DIAGNOSING A COMPLEX OF ON-BOARD EQUIPMENT OF AIRCRAFT BASED ON MACHINE LEARNING AND A DEVICE FOR ITS IMPLEMENTATION | 2023 |
|
RU2816667C1 |
| VIRTUAL STREAM COMPUTER SYSTEM BASED ON INFORMATION MODEL OF ARTIFICIAL NEURAL NETWORK AND NEURON | 2012 |
|
RU2530270C2 |
| METHOD FOR DIAGNOSING AIRCRAFT ON-BOARD EQUIPMENT COMPLEX BASED ON MACHINE LEARNING | 2023 |
|
RU2809719C1 |
| METHOD FOR DETECTING NORMAL REACTIONS OF COMPUTER NETWORK NODES TO NETWORK PACKETS RELATED TO UNKNOWN TRAFFIC | 2022 |
|
RU2802164C1 |
| OPTICAL CHARACTER RECOGNITION BY MEANS OF COMBINATION OF NEURAL NETWORK MODELS | 2020 |
|
RU2768211C1 |
