Abstract: A system and method for increasing the accuracy of time delay estimates of signals propagating through an environment. The system includes one or more sensors for receiving a plurality of signals, and a time delay estimator for measuring time delays between multiple pairs of signals. At least some of the multiple pairs of signals are received and measured at different points in time. The system further includes a data analyzer for analyzing time delay estimation data, for generating a statistical distribution of time delay estimates from the data, and for calculating a statistical estimate of time delay from the distribution. By increasing the number of signals employed by the system, the accuracy of the time delay estimation is increased. Further, by calculating the median or the mode of the statistical distribution, noise tolerance is improved.

Abstract: A system and method for estimating the SNR in a sonar environment and for determining the effect of the estimated SNR on sonar ranging accuracy. The system includes a sensor, a transmitter, a receiver, a plurality of band-pass filters, a cross correlator, and a data analyzer. The transmitter transmits a first signal having a predetermined frequency range through a transmission medium. The sensor generates a second signal corresponding to an echo signal reflected from an object. The first and second signals are provided to the band-pass filters, each operative to pass a respective sub-band of frequencies. The filters provide filtered versions of the first and second signals to the cross correlator, which performs cross correlation operations on the filtered signals. A data analyzer analyzes the cross correlator output data to determine the variability of cross correlation peaks within each frequency sub-band, thereby allowing more accurate SNR estimations in noisy environments.

Abstract: A system and method of performing sonar range estimations in a noisy sonar environment. The system includes a sensor, a transmitter, a receiver, a plurality of band-pass filters, a cross correlator, and a data analyzer. The transmitter transmits a pulse through a transmission medium. The pulse travels through the transmission medium until it strikes an object, which returns an echo to the sensor. The sensor provides the echo to the receiver, which provides an indication of the echo to the band-pass filters. The respective band-pass filters provide filtered versions of the echo and pulse to the cross correlator, which performs multiple cross correlation operations on the filtered echo and pulse. The cross correlator provides output data to the data analyzer, which uses the data to estimate the SNR in the environment and to determine a pulse center frequency corresponding to the estimated SNR.

Abstract: A recognition system is disclosed, including a representation of an object in terms of its constituent parts that is translationally invariant, and which provides scale invariant recognition. The system further provides effective recognition of patterns that are partially present in the input signal, or that are partially occluded, and also provides an effective representation for sequences within the input signal. The system utilizes dynamically determined, context based expectations, for identifying individual features/parts of an object to be recognized. The system is computationally efficient, and capable of highly parallel implementation, and further includes a mechanism for improving the preprocessing of individual sections of an input pattern, either by applying one or more preprocessors selected from a set of several preprocessors, or by changing the parameters within a single preprocessor.

Abstract: A system for separating and identifying classes of patterns or events which are not necessarily linearly separable. During a training process of the system, new prototypes are created when prior stored prototypes fail to properly classify an input pattern, and previously stored prototypes are modified when an input pattern falls within the sphere of influence of a prototype associated with a different class than the input pattern.

Abstract: A system is disclosed for separating and identifying classes of patterns or events which are not necessarily linearly separable. The patterns are represented by an input signal S. The system comprises (1) a plurality of classification units, connected in parallel to receive the input signal S and (2) a class selection device, responsive to the output signals produced by the classification units, for producing a single output response R representing the class of each respective pattern. At least some of the pattern classification units include generalizer units having a memory for storing a number of generalizer "prototypes" and a comparator for comparing the vector location of an input pattern with each of the generalizer prototypes.

Abstract: A system is disclosed for separating and identifying classes of patterns or events which are not necessarily linearly separable. The patterns are represented by an input signal S. The system comprises (1) a plurality of classification units, connected in parallel to receive the input signal S, and (2) a class selection device, responsive to the output signals produced by the classification units, for producing a single output response R representing the class of each respective pattern. In a preferred embodiment each classification unit includes a pattern feature encoding device, responsive to the input signal S, for producing an intermediate signal F.sub.i representative of the features contained in the pattern, and a pattern classifier, responsive to the signal F.sub.i, for producing an output signal R.sub.i representative of the respective class of the pattern, as identified by the features encoded by the feature encoding device.

Abstract: A system is provided for the separation into and the indentification of classes of events wherein each of the events is represented by a signal vector comprising the signals s, s.sub.z . . . , s.sub.j . . . , s.sub.N. The system comprises a plurality of assemblies, each of the assemblies including a matrix of junction elements for respectively receiving as inputs the different respective signals of a vector. The junction elements provide a transfer of information A.sub.ij s,; i.e., the product of the transfer function of the element and the signal input applied thereto. The information transferred by the junction elements is summed in each assembly. In the training mode of operation information summed in each assembly is applied to a scalar multiplier and the resulting information is in turn applied to a threshold stage which is actuated to produce an output if the input applied thereto attains a prescribed value.

Abstract: A curve follower or line tracing system for converting the common representation of patterns of lines into features which are readily usable as inputs to an adaptive information processing system such as a Nestor adaptive module. The problem addressed by this system is how to sequentially identify, from a global exposure or tracing of a curve, the starting and subsequent points of the curve in the same manner as tracing it by hand. In the curve follower, an array of light sensitive elements located on a grid identify a line at the grid points. Since the end point of the line has a single neighbor, it is readily located. The identification of an end point is used to subsequently inhibit further identification of the end point and create another point which is similar identified. Overall biases may be employed to define a preferred line direction. Once the resulting sequence is obtained, the line may be coded.

Abstract: An adaptive information processing system includes input terminals adapted to receive N input signals s.sub.1, s.sub.2, . . . s.sub.N representing an "input"; output terminals adapted to present n output responses r.sub.1, R.sub.2, . . . r.sub.n representing a "response"; and information processing apparatus, connecting the input with the output terminals, and operative to carry out the processing steps required to "map" different inputs into responses in accordance with a particular passive modification algorithm. This algorithm permits the recognition of unknown inputs and separates inputs which are in different classes but which are originally close to one another.

Abstract: A digital adaptive information processing system which executes the algorithm described in our U.S. Pat. No. 3,950,733 issued April 13, 1976. The system includes a digital input register adapted to receive and store N numbers s.sub.1, s.sub.2, . . . s.sub.N representing an input signal; a digital output register adapted to receive and store n numbers r.sub.1, r.sub.2, . . . r.sub.n representing an output response; and digital information processing apparatus, connecting the input register with the output register, and operative to carry out the processing steps required to "map" the numbers stored in the input register into numbers placed in storage in the output register in accordance with the aforementioned algorithm.

Abstract: An adaptive information processing system includes a module, called a Nestor module, having a plurality (N) of input terminals 1, 2 . . . , j . . . , N, adapted to receive N input signals s.sub.1, s.sub.2 . . . , s.sub.j . . . , S.sub.N, respectively, and a plurality (n) of output terminals 1, 2 . . . , i . . . , n, adapted to present n output responses r.sub.1, r.sub.2 . . . , r.sub.i . . . , r.sub.n, respectively. A plurality of junction elements, called mnemonders, couple various ones (or a multiplicity) of the input terminals with various ones (or a multiplicity) of the output terminals. These mnemonders provide a transfer of information from an input terminal j to an output terminal i in dependence upon the signal s.sub.j appearing at the input terminal j and upon the mnemonder transfer function A.sub.ij. Means are provided for modifying the transfer function A.sub.