{"title":"Use of Stochastic Automata for Parameter Self-Optimization with Multimodal Performance Criteria","authors":"I. Shapiro, K. Narendra","doi":"10.1109/TSSC.1969.300228","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300228","url":null,"abstract":"The application of stochastic automata to adaptive parameter optimization problems is considered. The fundamental problem is that of relating the concepts of automata theory and mathematical psychology learning theory to the usual notion of a performance index in a control system. Consideration is given to a number of possible automata structures, linear and nonlinear. One particular linear model is derived with optimal rather than expedient properties of convergence. A basic feature of this model is that it is based on a system response set of rewards and inactions, the latter being substituted for the more common penalty responses. This choice of response set is directly related to the achievement of the desired behavior. Simulations are described for the maximization of multimodal performance functions intentionally constructed to demonstrate the use of the method in situations where relative extrema occur. An example is also given of the automaton as a direct adaptive controller for a third order control system.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115349097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"System Identification with Threshold Measurements","authors":"A. Troelstra","doi":"10.1109/TSSC.1969.300224","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300224","url":null,"abstract":"A method has been developed to analyze systems which have threshold properties. The only information about the system response that is used in the analysis is whether or not this response exceeds a fixed threshold of unknown magnitude. There are many biological systems that fall into this category of systems, for example, the auditory system, the visual system, electrical stimulation of nerve cells, etc. However, any network to which an arbitrary amplitude has been assigned and which the response has to exceed as an artificial threshold could be analyzed with the methods outlined in this paper. The cases of a simple linear system and first- and second-order photochemical reactions are discussed extensively. It is shown that due to the limited output information available, often no unique system characterization is possible. However, the method can be a powerful aid in the selection between various alternatives. The influence of possible nonlinear operators in the system has been analyzed, and the result turns out to be very dependent upon the location and character of these operators. Some classic vision-research experiments are discussed as examples to illustrate the application of the analysis put forward in this paper.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126535024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automatic Analysis of Sleep Electroencephalograms by Hybrid Computation","authors":"Jack R. Smith, M. Negin, A. H. Nevis","doi":"10.1109/TSSC.1969.300220","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300220","url":null,"abstract":"An automated sleep electroencephalogram (EEG) analyzer has been designed and tested in an effort to eliminate tedious and variable human interpretation of experimental EEG data. Data is presented to a hybrid computer from EEG tapes recorded during experimental studies in a human sleep laboratory. Special analog filters are used to identify specific transient waveforms in the EEG. Bandpass filters are used to detect the rhythmical waveforms. The outputs of these filters are then processed by digital logic circuitry, whose algorithms emulate the rules used by human readers quantitating the level of sleep each minute according to the EEG pattem. Preliminary results give 89-percent correlation with a minute-by-minute comparison to the human evaluation of the same test EEG.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130516428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Formulation of Fuzzy Automata and Its Application as a Model of Learning Systems","authors":"W. Wee, K. Fu","doi":"10.1109/TSSC.1969.300263","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300263","url":null,"abstract":"Based on the concept of fuzzy sets defined by Zadeh, a class of fuzzy automata is formulated similar to Mealy's formulation of finite automata. A fuzzy automaton behaves in a deterministic fashion. However, it has many properties similar to that of stochastic automata. Its application as a model of learning systems is discussed. A nonsupervised learning scheme in automatic control and pattern recognition is proposed with computer simulation results presented. An advantage of employing fuzzy automaton as a learning model is its simplicity in design and computation.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123423648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Electrochemically Active Field-Trainable Pattern Recognition Systems","authors":"R. M. Stewart","doi":"10.1109/TSSC.1969.300265","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300265","url":null,"abstract":"System performance tests have recently been carried out on an experimental electrochemically active/plastic system designed to demonstrate and begin to explore the theoretically predicted phenomenon we call temporally associative \"field-trainability,\" a process which, when perfected and extended, may lead to revolutionary advances in manufacturing ultrahigh-density and highly versatile pattern recognition machines. The first complete experimental system, called-linear field-trainable, (LIFT) consists of two matching but opposing (excitatory/inhibitory) parallel arrays of active/plastic dipoles (iron/gold) in nitric acid, which are stimulated (electrically) in various patterns of activity. and respond by simple parallel coupling through the surrounding fluids and steel container walls to a low-impedance low-pass threshold detector. Alternatively, when desired, the chambers are connected to a power supply, the effect of which is to deliver massive electrical shocks to the entire array at once. The resulting reinforcement field is applied in synchronism with sample input pattern stimulations (which alternate with unreinforced response test stimulations) in attempts to induce at will, in a sequence of small steps, simultaneous changes of fine cellular structure which will produce corresponding specific systemic functional mutations as desired from among the class of linear decision functions.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"11 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133989013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correction to \"On the Inverse of Linear Dynamical Systems\"","authors":"P. Dorato","doi":"10.1109/TSSC.1969.300272","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300272","url":null,"abstract":"quiring most development. Assuming that step 3 provided a vector measurement of the regional change envisioned, the districts may be ranked by magnitude of this vector and the implementation staged accordingly. For planniing purposes it may be useful to estimate crudely the socioeconomic vectors at intermediate time periods. Fig. 3 shows a simple straight-line growth curve interpolated between BT (time for implementation of the service in this district) and Ao.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123528699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stochastic Allocation and System Analysis","authors":"A. Klinger","doi":"10.1109/TSSC.1969.300262","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300262","url":null,"abstract":"The optimum allocation of a fixed stock of unreliable units to a random number of demands is discussed. The demands occur at Poisson times; several types of criteria are described, but the most important optimum presented is of the probability that at least one allotted unit does not fail at every Poisson demand. Hence this concerns how unreliable elements can best be used to create a reliable system. The allocation problem arose in a military system analysis context. The results presented exemplify how system science concepts (Poisson models, recursive computation, and cost/ benefit comparisons) and current computing tools can be applied to practical problems.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128973447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Some New Approaches to Machine Learning","authors":"N. Findler","doi":"10.1109/TSSC.1969.300258","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300258","url":null,"abstract":"Five different but interrelated models of learning have been established within a complex computer program. These models incorporate mechanisms that optimize response patterns on algorithmic and heuristic bases; make abstractions at different levels; produce value judgements; recognize, modify, store, and retrieve geometrical patterns; and exhibit, in general, many aspects of intelligent behavior. Both the teacher and the learner are simulated in the machine. In one model, the program follows a qualitatively new kind of learning process in generating its own strategy and improving it on the basis of experience. The method enables the learner to exceed the playing quality of the teacher. It is suggested that the methods and techniques employed in the project may be useful in mechanizing some problem-solving activities that can be reduced to pattern recognition, such as meteorological forecasting, medical diagnosis, traffic control, and so on. No deliberate attempt has been made to imitate humans.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115215329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Constraint Theory, Part III: Inequality and Discrete Relations","authors":"G. Friedman, C. Leondes","doi":"10.1109/TSSC.1969.300260","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300260","url":null,"abstract":"Parts I and II of this three-part paper provided the fundamental concepts underlying constraint theory whose goal is the systematic determination of whether a mathematical model and its computations are well posed. In addition to deriving results for the general relation, special relations defined as universal and regular were treated. This concluding part treats two more special relations: inequality and discrete. Employing the axiom of transitivity for inequalities, results relating to the consistency of a mathematical model of inequalities in terms of its model graph are derived. Rules for the simultaneous propagation of four types of constraint, over, point, interval, and slack, through a heterogeneous model graph are established. In contrast to other relation types, discrete relations point constrain every relevant variable, so that finding intrinsic constraint sources is trivial. A general procedure is provided to determine the allowability of requested computations on a discrete model.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116567683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of Optimal Control Theory to the Crashworthiness of a Passenger Vehicle Model","authors":"H. Kaufman, D. B. Larson","doi":"10.1109/TSSC.1969.300270","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300270","url":null,"abstract":"Optimal control theory concepts are thought to be useful in understanding the problem of determining safe deceleration characteristics for a crashing vehicle. These deceleration waveforms are to be computed such that passenger belt forces are minimized. Using both a linear one-degree-of-freedom model and a nonlinear two-degree-of-freedom model for a frontal collision, this problem is shown to be equivalent to the minimization of a performance or cost function when the terminal time is not fixed a priori, but is determined by terminal constraints. While the maximum principle is applied directly to find the optimal deceleration waveform for the linear problem, the steepest ascent method is used to optimize iteratively the nonlinear problem. Passenger seatbelt forces which resulted from using these optimal waveforms were compared with those forces which resulted from using step and ramp functions. Results showed that the seat belt forces resulting from the optimally derived deceleration signals were considerably smaller than those using step and ramp functions. With further effort, these results could possibly be used as design guides.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133938112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}