US 2022/0027408 A1 · MEMORY OF SEQUENCES, METHOD FOR CREATION AND FUNCTIONING OF SEQUENCE MEMORY, HIERARCHICAL SEQUENCE MEMORY

Abstract

Sequence Memory is intended for entering sequences and creating a statistical map of the weights of the joint occurrence of sequence objects and analyzing the map for solving problems: 1) predicting the appearance of the next sequence objects in the past or future; 2) determining the context and the point of changing the context of the sequence with the assignment of individual sections of the sequence unique identifiers of the context; 3) input of sequences of context identifiers in the Sequence Memory of the next level of the hierarchy in order to create a Hierarchical Sequence Memory; 4) Representation of cause-and-effect relationships as relationships of mutual occurrence of objects of different levels of the hierarchy for analysis 5) identification of cause-and-effect relationships of the corresponding level of the hierarchy for making conclusions and judgments. The Sequence Memory Device and the Hierarchical Sequence Memory device are designed to reduce the complexity of solving the problems of the Sequence Memory and the Hierarchical Sequence Memory. The Sequence Memory device is a fully connected crossbar of two intersecting sets of transverse buses, each of which encodes one of the unique sequence objects, and the connection weight of each two objects is encoded by the Artificial Neurons of Occurrence (INV) set at the intersection of the corresponding buses. The Hierarchical Sequence Memory device connects two or more Sequence Memory devices of sequential hierarchy levels connected by a plurality of Artificial Neurons of the Hierarchy, as well as layers of measurement buses associated with the Hierarchical Sequence Memory through Artificial Neurons of the Label, providing 1) representation of a sequence of contexts of sequence objects through Sequence Memory buses, connection of sequence objects through INV, shorter sequences of contexts at different levels of the hierarchy, 2) assignment of measurement labels in order to compare and synchronize sequences with comparable measurement labels.

Claims19

Dependent claims

A method of creation and functioning of the sequence memory wherein digital information is represented by a plurality of machine-readable data arrays, each of which is a sequence of unique objects, each represented by a unique machine-readable value of the object, and each unique object (hereinafter the “key object”) appears, at least in some sequences, the sequence memory is trained by feeding the sequences of objects to the memory input, and each time the key object appears, the memory extracts the objects preceding the key object in the sequence (hereinafter referred to as “frequent objects of the past”), increases by one the value of the counter of the co-occurrence of the key object with each unique frequent object of the past and updates the counter value with a new value, and combines the counter values for different unique frequent objects into a data array of weights of the “past”, as well the memory, at each appearance of the key object, extracts from the named sequence the objects following the named key object in the named sequence (hereinafter referred to as “frequent objects of the future”), increases by one the value of the counter of the mutual occurrence of the key object with each unique frequent object and updates the counter value with a new value, and combines the counter values for different unique frequent objects into a data array of weights of the “future”;

each data array of “past” and “future” is being divided into subsets (hereinafter “rank sets”), each of which contains only frequent objects equidistant from the named key object either in the “past” or in the “future”, and each unique key object with at least one corresponding rank set is put in the sequence memory;
and the sequence memory provides a search in the named data arrays for the named rank set of weights in response to the input of the named unique key object or the search for the named unique key object in response to the input of the rank set or its part.

A sequence memory (hereinafter «PP») containing two interconnected sets of N parallel numbered buses, of which the first set is located above the second set so that the buses of the first and second sets form intersections (crossbar), where the ends of each set of buses located on one of the sides of the crossbar are used as inputs, and the opposite ends are used as outputs so that the signals applied to the inputs of the first set of buses are read both from the outputs of the first set of buses, and from the outputs of the second set buses in the presence of commutative elements in the intersection of the first and second set;

the angle β{circumflex over ( )}0 between the buses of the first and second sets is chosen, based on the functional and geometric requirements for the memory device, wherein, the buses of the first and second sets with the same numbers are connected to each other at their intersection so that the set of such connections forms a diagonal of the matrix, dividing the crossbar into two symmetric triangular semi-crossbars (hereinafter referred to as “Triangles”), at least one of which (hereinafter the “First Triangle”) is used by connecting each two buses, at least with mismatching numbers from the first and second sets at their intersection by means of at least one Artificial Neuron of Occurrence (INV) so that the ends of the buses of the first set are inputs and the ends of the second set of buses are outputs of the Triangle, and INV is used as the named Switching Element for accumulating, storing and reading the weight of the co-occurrence of objects to which the buses connected by the named INV correspond;
each of said INVs functions at least as a counter with an activation function and a memory cell for storing the last value and the value of the INV activation threshold;
before starting the device operation, the last value is assigned some initial value, which is saved in the memory cell of the Counter;
the value of the INV activation threshold is also stored in the memory cell;
in the learning mode, each time when signals are applied simultaneously to each of the buses connected by means of the INV, the named INV measures one of the signal characteristics on each of their buses, then compares the measured values of the characteristics and, if the comparison result corresponds to the value of the INV activation threshold, the INV reads the last value from the memory cell, increases the named last value by the amount of change in the occurrence and stores the new last value in the memory cell, and in the playback mode the signal is fed to at least one of the named buses connected by means of the INV, the signal is passed through the INV, where from the memory cell the last value is extracted, one of the signal characteristics is changed according to the extracted last value, and the named modified signal is transmitted to the second of the named buses connected by means of the INV, to extract the named last value from the named one of the signal characteristics and use the named last values as the weight of the co-occurrence of objects to which the buses correspond.

2 more elements

Dependencies are inferred from the claim text.

Memory of sequences, method for creation and functioning of sequence memory, hierarchical sequence memory

Life of this patent

Memory of sequences, method for creation and functioning of sequence memory, hierarchical sequence memory

Life of this patent

Abstract

Claims19