Remove unneccessary Random in EMG example (#156)

The EMG hand gestures example uses a Random embedding to encode the
timestamp. However, the paper does not use such embedding and the
timing is encoded by permuting the spatial samples.

examples/emg_hand_gestures.py

@@ -33,13 +33,11 @@ def __init__(self, out_features, timestamps, channels):
         super(Encoder, self).__init__()
 
         self.channels = embeddings.Random(channels, out_features)
-        self.timestamps = embeddings.Random(timestamps, out_features)
         self.signals = embeddings.Level(NUM_LEVELS, out_features, high=20)
 
     def forward(self, input: torch.Tensor) -> torch.Tensor:
         signal = self.signals(input)
         samples = torchhd.bind(signal, self.channels.weight.unsqueeze(0))
-        samples = torchhd.bind(samples, self.timestamps.weight.unsqueeze(1))
 
         samples = torchhd.multiset(samples)
         sample_hv = torchhd.ngrams(samples, n=N_GRAM_SIZE)