Add missing asm and ass

jAbsoluteValueOfTheSummationOfExpRoot.m

@@ -0,0 +1,17 @@
+%[2018]-Pattern recognition of electromyography signals based on novel
+%time domain features for amputees’ limb motion classification" (3)
+
+function ASM = jAbsoluteValueOfTheSummationOfExpRoot(X,~)
+K = length(X); 
+Y = 0; 
+for n = 1:K
+ if n >= 0.25 * K && n <= 0.75 * K
+ exp = 0.5;
+ else
+ exp = 0.75;
+ end
+ Y = Y + (X(n) ^ exp);
+end
+ASM = abs(Y / K);
+end
+

jAbsoluteValueOfTheSummationOfSquareRoot.m

@@ -0,0 +1,8 @@
+%[2018]-Pattern recognition of electromyography signals based on novel
+%time domain features for amputees’ limb motion classification" (1)
+
+function ASS = jAbsoluteValueOfTheSummationOfSquareRoot(X,~)
+temp = sum(X .^ (1/2));
+ASS = abs(temp);
+end
+

jfemg.m

@@ -1,12 +1,12 @@
-% Feature Extraction Toolbox by Jingwei Too - 11/12/2020
+% Feature Extraction Toolbox by Jingwei Too 
 
 function feat = jfemg(type,X,opts)
 switch type
  case 'fzc' ; fun = @jNewZeroCrossing;
  case 'ewl' ; fun = @jEnhancedWaveLength;
  case 'emav' ; fun = @jEnhancedMeanAbsoluteValue; 
- case 'ass' ; fun = @jAbsoluteValueOfTheSummation;
- case 'asm' ; fun = @jAbsoluteValueOfTheSummationOfSquareRoot;
+ case 'asm' ; fun = @jAbsoluteValueOfTheSummationOfExpRoot;
+ case 'ass' ; fun = @jAbsoluteValueOfTheSummationOfSquareRoot;
  case 'msr' ; fun = @jMeanValueOfTheSquareRoot;
  case 'ltkeo' ; fun = @jLogTeagerKaiserEnergyOperator; 
  case 'lcov' ; fun = @jLogCoefficientOfVariation;